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Introduction to Logistics Systems Planning and Control


Advisory Editors

Sheldon Ross
Department of Industrial Engineering and Operations Research, University of California,
Berkeley, CA 94720, USA
Richard Weber
Statistical Laboratory, Centre for Mathematical Sciences, Cambridge University,
Wilberforce Road, Cambridge CB3 0WB

BATHER “ Decision Theory: An Introduction to Dynamic Programming and Sequential
CHAO/MIYAZAWA/PINEDO “ Queueing Networks: Customers, Signals and Product Form
COURCOUBETIS/WEBER “ Pricing Communication Networks: Economics, Technology
and Modelling
DEB “ Multi-Objective Optimization using Evolutionary Algorithms
GERMAN “ Performance Analysis of Communication Systems: Modeling with
Non-Markovian Stochastic Petri Nets
GHIANI/LAPORTE/MUSMANNO “ Introduction to Logistics Systems Planning and
KALL/WALLACE “ Stochastic Programming
KAMP/HASLER “ Recursive Neural Networks for Associative Memory
KIBZUN/KAN “ Stochastic Programming Problems with Probability and Quantile Functions
RUSTEM “ Algorithms for Nonlinear Programming and Multiple-Objective Decisions
WHITTLE “ Optimal Control: Basics and Beyond
WHITTLE “ Neural Nets and Chaotic Carriers

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in areas of interest, or associated methodology.

Introduction to Logistics Systems Planning and Control

Gianpaolo Ghiani
Department of Innovation Engineering,
University of Lecce, Italy
Gilbert Laporte
Canada Research Chair in Distribution Management,
HEC Montr´ al, Canada
Roberto Musmanno
Department of Electronics, Informatics and Systems,
University of Calabria, Italy

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Library of Congress Cataloguing-in-Publication Data
Ghiani, Gianpaolo.
Introduction to logistics systems planning and control / Gianpaolo Ghiani,
Gilbert Laporte, Roberto Musmanno.
p. cm. “ (Wiley-Interscience series in systems and optimization)
Includes bibliographical references and index.
ISBN 0-470-84916-9 (alk. paper) “ ISBN 0-470-84917-7 (pbk.: alk. paper)
1. Materials management. 2. Materials handling. I. Laporte, Gilbert. II. Musmanno, Roberto. III. Title.
IV. Series.
TS161.G47 2003
658.7“dc22 2003057594
British Library Cataloguing in Publication Data
A catalogue record for this book is available from the British Library
ISBN 0-470-84916-9 (Cloth)
0-470-84917-7 (Paper)

Produced from L TEX ¬les supplied by the authors, typeset by T&T Productions Ltd, London.
Printed and bound in Great Britain by TJ International, Padstow, Cornwall.
This book is printed on acid-free paper responsibly manufactured from sustainable forestry
in which at least two trees are planted for each one used for paper production.

To Laura

To Ann and Cathy
To Maria Carmela, Francesco and Andrea


Foreword xiii

Preface xv

Abbreviations xvi

Problems and Website xix

Acknowledgements xxi

About the Authors xxiii

1 Introducing Logistics Systems 1
1.1 Introduction 1
1.2 How Logistics Systems Work 6
1.2.1 Order processing 6
1.2.2 Inventory management 6
1.2.3 Freight transportation 9
1.3 Logistics Managerial Issues 14
1.4 Emerging Trends in Logistics 16
1.5 Logistics Decisions 18
1.5.1 Decision support methods 18
1.5.2 Outline of the book 20
1.6 Questions and Problems 20
1.7 Annotated Bibliography 22

2 Forecasting Logistics Requirements 25
2.1 Introduction 25
2.2 Demand Forecasting Methods 28
2.2.1 Qualitative methods 28
2.2.2 Quantitative methods 29


2.2.3 Notation 30
2.3 Causal Methods 30
2.4 Time Series Extrapolation 33
2.4.1 Time series decomposition method 34
2.5 Further Time Series Extrapolation Methods: the Constant
Trend Case 41
2.5.1 Elementary technique 42
2.5.2 Moving average method 44
2.5.3 Exponential smoothing method 48
2.5.4 Choice of the smoothing constant 49
2.5.5 The demand forecasts for the subsequent time periods 49
2.6 Further Time Series Extrapolation Methods: the Linear
Trend Case 50
2.6.1 Elementary technique 50
2.6.2 Linear regression method 51
2.6.3 Double moving average method 52
2.6.4 The Holt method 53
2.7 Further Time Series Extrapolation Methods: the Seasonal
Effect Case 54
2.7.1 Elementary technique 55
2.7.2 Revised exponential smoothing method 56
2.7.3 The Winters method 58
2.8 Advanced Forecasting Methods 61
2.9 Selection and Control of Forecasting Methods 64
2.9.1 Accuracy measures 64
2.9.2 Forecast control 65
2.10 Questions and Problems 67
2.11 Annotated Bibliography 72

3 Designing the Logistics Network 73
3.1 Introduction 73
3.2 Classi¬cation of Location Problems 74
3.3 Single-Echelon Single-Commodity Location Models 77
3.3.1 Linear transportation costs and facility ¬xed costs 79
3.3.2 Linear transportation costs and concave piecewise
linear facility operating costs 90
3.4 Two-Echelon Multicommodity Location Models 95
3.5 Logistics Facility Location in the Public Sector 107
p-centre models
3.5.1 108
3.5.2 The location-covering model 111
3.6 Data Aggregation 115
3.7 Questions and Problems 118
3.8 Annotated Bibliography 119


4 Solving Inventory Management Problems 121
4.1 Introduction 121
4.2 Relevant Costs 121
4.3 Classi¬cation of Inventory Management Models 123
4.4 Single Stocking Point: Single-Commodity Inventory
Models under Constant Demand Rate 123
4.4.1 Noninstantaneous resupply 124
4.4.2 Instantaneous resupply 128
4.4.3 Reorder point 130
4.5 Single Stocking Point: Single-Commodity Inventory
Models under Deterministic Time-Varying Demand Rate 130
4.6 Models with Discounts 132
4.6.1 Quantity-discounts-on-all-units 132
4.6.2 Incremental quantity discounts 134
4.7 Single Stocking Point: Multicommodity Inventory Models 136
4.7.1 Models with capacity constraints 136
4.7.2 Models with joint costs 138
4.8 Stochastic Models 141
4.8.1 The Newsboy Problem 141
The (s, S) policy for single period problems
4.8.2 142
4.8.3 The reorder point policy 143
4.8.4 The periodic review policy 145
The (s, S) policy
4.8.5 146
4.8.6 The two-bin policy 147
4.9 Selecting an Inventory Policy 148
4.10 Multiple Stocking Point Models 149
4.11 Slow-Moving Item Models 152
4.12 Policy Robustness 153
4.13 Questions and Problems 154
4.14 Annotated Bibliography 155

5 Designing and Operating a Warehouse 157
5.1 Introduction 157
5.1.1 Internal warehouse structure and operations 159
5.1.2 Storage media 160
5.1.3 Storage/retrieval transport mechanisms and policies 161
5.1.4 Decisions support methodologies 165
5.2 Warehouse Design 165
5.2.1 Selecting the storage medium and the
storage/retrieval transport mechanism 166
5.2.2 Sizing the receiving and shipment subsystems 166
5.2.3 Sizing the storage subsystems 166
5.3 Tactical Decisions 174


5.3.1 Product allocation 174
5.4 Operational Decisions 180
5.4.1 Batch formation 181
5.4.2 Order picker routing 184
5.4.3 Packing problems 185
5.5 Questions and Problems 195
5.6 Annotated Bibliography 198

6 Planning and Managing Long-Haul Freight
Transportation 199
6.1 Introduction 199
6.2 Relevant Costs 200
6.3 Classi¬cation of Transportation Problems 201
6.4 Fleet Composition 204
6.5 Freight Traf¬c Assignment Problems 206
6.5.1 Minimum-cost ¬‚ow formulation 207
6.5.2 Linear single-commodity minimum-cost ¬‚ow problems 209
6.5.3 Linear multicommodity minimum-cost ¬‚ow problems 217
6.6 Service Network Design Problems 224
6.6.1 Fixed-charge network design models 225
6.6.2 The linear ¬xed-charge network design model 226
6.7 Shipment Consolidation and Dispatching 233
6.8 Freight Terminal Design and Operations 236
6.8.1 Design issues 236
6.8.2 Tactical and operational issues 237
6.9 Vehicle Allocation Problems 239
6.10 The Dynamic Driver Assignment Problem 241
6.11 Questions and Problems 243
6.12 Annotated Bibliography 244

7 Planning and Managing Short-Haul Freight
Transportation 247
7.1 Introduction 247
7.2 Vehicle Routing Problems 249
7.3 The Travelling Salesman Problem 252
7.3.1 The asymmetric travelling salesman problem 252
7.3.2 The symmetric travelling salesman problem 257
7.4 The Node Routing Problem with Capacity and Length
Constraints 265
7.4.1 Constructive heuristics 269
7.5 The Node Routing and Scheduling Problem with Time Windows 273
7.5.1 An insertion heuristic 274


7.5.2 A uni¬ed tabu search procedure for constrained
node routing problems 278
7.6 Arc Routing Problems 281
7.6.1 The Chinese postman problem 281
7.6.2 The rural postman problem 286
7.7 Real-Time Vehicle Routing and Dispatching 291
7.8 Integrated Location and Routing 294
7.9 Vendor-Managed Inventory Routing 294
7.10 Questions and Problems 296
7.11 Annotated Bibliography 297

8 Linking Theory to Practice 299
8.1 Introduction 299
8.2 Shipment Consolidation and Dispatching at ExxonMobil
Chemical 300
8.3 Distribution Management at P¬zer 302
8.3.1 The Logistics System 303
8.3.2 The Italian ALFA10 distribution system 305
8.4 Freight Rail Transportation at Railion 307
8.5 Yard Management at the Gioia Tauro Marine Terminal 308
8.6 Municipal Solid Waste Collection and Disposal
Management at the Regional Municipality of
Hamilton-Wentworth 312
8.7 Demand Forecasting at Adriatica Accumulatori 312
8.8 Distribution Logistics Network Design at DowBrands 314
8.9 Container Warehouse Location at Hardcastle 317
8.10 Inventory Management at Wolferine 321
8.11 Airplane Loading at FedEx 322
8.12 Container Loading at Waterworld 324
8.12.1 Packing rolls into containers 324
8.12.2 Packing pallets into containers 325
8.13 Air Network Design at Intexpress 325
8.14 Bulk-Cargo Ship Scheduling Problem at the US Navy 330
8.15 Meter Reader Routing and Scheduling at Socal 332
8.16 Annotated Bibliography 334
8.17 Further Case Studies 336

Index 339


Logistics is concerned with the organization, movement and storage of material and
people. The term logistics was ¬rst used by the military to describe the activities
associated with maintaining a ¬ghting force in the ¬eld and, in its narrowest sense,
describes the housing of troops. Over the years the meaning of the term has grad-
ually generalized to cover business and service activities. The domain of logistics
activities is providing the customers of the system with the right product, in the right
place, at the right time. This ranges from providing the necessary subcomponents for
manufacturing, having inventory on the shelf of a retailer, to having the right amount
and type of blood available for hospital surgeries. A fundamental characteristic of
logistics is its holistic, integrated view of all the activities that it encompasses. So,
while procurement, inventory management, transportation management, warehouse
management and distribution are all important components, logistics is concerned
with the integration of these and other activities to provide the time and space value
to the system or corporation.
Excess global capacity in most types of industry has generated intense competition.
At the same time, the availability of alternative products has created a very demanding
type of customer, who insists on the instantaneous availability of a continuous stream
of new models. So the providers of logistics activities are asked to do more transac-
tions, in smaller quantities, with less lead time, in less time, for less cost, and with
greater accuracy. New trends such as mass customization will only intensify these
demands. The accelerated pace and greater scope of logistics operations has made
planning-as-usual impossible.
Even with the increased number and speed of activities, the annual expenses asso-
ciated with logistics activities in the United States have held constant for the last
several years around ten per cent of the gross domestic product. Given the signi¬cant
amounts of money involved and the increased operational requirements, the planning
and control of logistics systems has gained widespread attention from practitioners
and academic researchers alike. To maximize the value in a logistics system, a large
variety of planning decisions has to be made, ranging from the simple warehouse-¬‚oor
choice of which item to pick next to ful¬l a customer order to the corporate-level deci-
sion to build a new manufacturing plant. Logistics planning supports the full range
of those decisions related to the design and operation of logistics systems.


There exists a vast amount of literature, software packages, decision support tools
and design algorithms that focus on isolated components of the logistics system or
isolated planning in the logistics systems. In the last two decades, several companies
have developed enterprise resource planning (ERP) systems in response to the need of
global corporations to plan their entire supply chain. In their initial implementations,
the ERP systems were primarily used for the recording of transactions rather than
for the planning of resources on an enterprise-wide scale. Their main advantage
was to provide consistent, up-to-date and accessible data to the enterprise. In recent
years, the original ERP systems have been extended with advanced planning systems
(APSs). The main function of APSs is for the ¬rst time the planning of enterprise-
wide resources and actions. This implies a coordination of the plans among several
organizations and geographically dispersed locations.
So, while logistics planning and control requires an integrated, holistic approach,
their treatment in courses and textbooks tends to be either integrated and qualita-
tive or mathematical and very speci¬c. This book bridges the gap between those
two approaches. It provides a comprehensive and modelling-based treatment of the
complete distribution system and process, including the design of distribution cen-
tres, terminal operations and transportation operations. The three major components
of logistics systems”inventory, transportation and facilities”are each examined in
detail. For each topic the problem is de¬ned, models and solution algorithms are
presented that support computer-assisted decision-making, and numerous applica-
tion examples are provided. The book concludes with an extensive set of case studies
that illustrate the application of the models and algorithms in practice. Because of
its rigorous mathematical treatment of real-world planning and control problems in
logistics, the book will provide a valuable resource to graduate and senior undergrad-
uate students and practitioners who are trying to improve logistics operations and
satisfy their customers.

Marc Goetschalckx
Georgia Institute of Technology
Atlanta, May 2003


Logistics is key to the modern economy. From the steel factories of Pennsylvania
to the port of Singapore, from the Nicaraguan banana ¬elds to postal delivery and
solid waste collection in any region of the world, almost every organization faces the
problem of getting the right materials to the right place at the right time. Increasingly
competitive markets are making it imperative to manage logistics systems more and
more ef¬ciently.
This textbook grew out of a number of undergraduate and graduate courses on
logistics and supply chain management that we have taught to engineering, computer
science, and management science students. The goal of these courses is to give students
a solid understanding of the analytical tools available to reduce costs and improve
service levels in logistics systems. For several years, the lack of a suitable textbook
forced us to make use of a number of monographs and scienti¬c papers which tended to
be beyond the level of most students. We therefore committed ourselves to developing
a quantitative textbook, written at a more accessible level.
The book targets both an educational audience and practitioners. It should be appro-
priate for advanced undergraduate and graduate courses in logistics, operations man-
agement, and supply chain management. It should also serve as a reference for prac-
titioners in consulting as well as in industry. We make the assumption that the reader
is familiar with the basics of operations research, probability theory and statistics.
We provide a balanced treatment of sales forecasting, logistics system design, inven-
tory management, warehouse design and management, and freight transport planning
and control. In the ¬nal chapter we present some insightful case studies, taken from
the scienti¬c literature, which illustrate the use of quantitative methods for solving
complex logistics decision problems.
In our text every topic is illustrated with a numerical example so that the reader
can check his or her understanding of each concept before going on to the next one.
In addition, a concise annotated bibliography at the end of each chapter acquaints the
reader with the state of the art in logistics.


1-BP One-Dimensional Bin Packing
2-BP Two-Dimensional Bin Packing
3-BP Three-Dimensional Bin Packing
3PL Third Party Logistics
AP Assignment Problem
ARP Arc Routing Problem
AS/RS Automated Storage and Retrieval System
ATSP Asymmetric Travelling Salesman Problem
B2B Business To Business
B2C Business To Consumers
BF Best Fit
BFD Best Fit Decreasing
BL Bottom Left
CDC Central Distribution Centre
CPL Capacitated Plant Location
CPP Chinese Postman Problem
DC Distribution Centre
DDAP Dynamic Driver Assignment Problem
EDI Electronic Data Interchange
EOQ Economic Order Quantity
EU European Union
FBF Finite Best Fit
FCFS First Come First Served
FCND Fixed Charge Network Design
FF First Fit
FFD First Fit Decreasing
FFF Finite First Fit
GIS Geographic Information System
GDP Gross Domestic Product
GPS Global Positioning Systems
IP Integer Programming


IRP Inventory-Routing Problem
ITR Inventory Turnover Ratio
KPI Key Performance Indicator
LB Lower Bound
LFND Linear Fixed Charge Network Design
LMCF Linear Single-Commodity Minimum-Cost Flow
LMMCF Linear Multicommodity Minimum-Cost Flow
LP Linear Programming
LTL Less-Than-Truckload
MAD Mean Absolute Deviation
MAP D Mean Absolute Percentage Deviation
MIP Mixed-Integer Programming
MMCF Multicommodity Minimum-Cost Flow
MRP Manufacturing Resource Planning
Minimum-cost Spanning r-Tree Problem
MSE Mean Squared Error
MTA Make-To-Assembly
MTO Make-To-Order
MTS Make-To-Stock
NAFTA North America Free Trade Agreement
NF Network Flow
NLP Nonlinear Programming
NMFC National Motor Freight Classi¬cation
NRP Node Routing Problem
NRPCL Node Routing Problem with Capacity and Length Constraints
NRPSC Node Routing Problem”Set Covering
NRPSP Node Routing Problem”Set Partitioning
NRSPTW Node Routing and Scheduling Problem With Time Windows
PCB Printed Circuit Board
POPITT Points Of Presence In The Territory
RDC Regional Distribution Centre
RPP Rural Postman Problem
RTSP Road Travelling Salesman Problem
S/R Storage And Retrieval
SC Set Covering
SCOR Supply Chain Operations References
SESC Single-Echelon Single-Commodity
SKU Stock Keeping Unit
SPL Simple Plant Location
STSP Symmetric Travelling Salesman Problem
TAP Traf¬c Assignment Problem


TEMC Two-Echelon Multicommodity
TEU Twenty-foot Equivalent Unit
TL Truckload
TS Tabu Search
TSP Travelling Salesman Problem
UB Upper Bound
VAP Vehicle Allocation Problem
VMR Vendor-Managed Resupplying
VRDP Vehicle Routing and Dispatching Problem
VRP Vehicle Routing Problem
VRSP Vehicle Routing and Scheduling Problem
W/RPS Walk/Ride and Pick Systems
ZIO Zero Inventory Ordering

Problems and Website

This textbook contains questions and problems at the end of every chapter. Some
are discussion questions while others focus on modelling or algorithmic issues. The
answers to these problems are available on the book™s website
which also contains additional material (FAQs, software, further modelling exercises,
links to other websites, etc.).


We thank all the individuals and organizations who helped in one way or another to
produce this textbook. First and most of all, we would like to thank Professor Lucio
Grandinetti (University of Calabria) for his encouragement and support. We are grate-
ful to the reviewers whose comments were invaluable in improving the organization
and presentation of the book. We are also indebted to Fabio Fiscaletti (P¬zer Phar-
maceuticals Group) and Luca Lenzi (ExxonMobil Chemical), who provided several
helpful ideas. In addition, we thank HEC Montr©al for its ¬nancial support. Our thanks
also go to Maria Teresa Guaglianone, Francesca Vocaturo and Sandro Zacchino for
their technical assistance, and to Nicole Paradis for carefully editing and proofreading
the material. Finally, the book would not have taken shape without the very capable
assistance of Rob Calver, our editor at Wiley.

About the Authors

Gianpaolo Ghiani is Associate Professor of Operations Research at the University of
Lecce, Italy. His main research interests lie in the ¬eld of combinatorial optimization,
particularly in vehicle routing, location and layout problems. He has published in a
variety of journals, including Mathematical Programming, Operations Research Let-
ters, Networks, Transportation Science, Optimization Methods and Software, Comput-
ers and Operations Research, International Transactions in Operational Research,
European Journal of Operational Research, Journal of the Operational Research
Society, Parallel Computing and Journal of Intelligent Manufacturing Systems. His
doctoral thesis was awarded the Transportation Science Dissertation Award from
INFORMS in 1998. He is an editorial board member of Computers & Operations
Gilbert Laporte obtained his PhD in Operations Research at the London School
of Economics in 1975. He is Professor of Operations Research at HEC Montr©al,
Director of the Canada Research Chair in Distribution Management, and Adjunct
Professor at the University of Alberta. He is also a member of GERAD, of the Centre
for Research on Transportation (serving as director from 1987 to 1991), and Fellow
of the Center for Management of Operations and Logistics, University of Texas at
Austin. He has authored or coauthored several books, as well as more than 225 sci-
enti¬c articles in combinatorial optimization, mostly in the areas of vehicle routing,
location, districting and timetabling. He is the current editor of Computers & Opera-
tions Research and served as editor of Transportation Science from 1995 to 2002. He
has received many scienti¬c awards including the Pergamon Prize (United Kingdom),
the Merit Award of the Canadian Operational Research Society, the CORS Practice
Prize on two occasions, the Jacques-Rousseau Prize for Interdisciplinarity, as well
as the President™s medal of the Operational Research Society (United Kingdom). In
1998 he became a member of the Royal Society of Canada.
Roberto Musmanno is Professor of Operations Research at the University of Cal-
abria, Italy. His major research interests lie in logistics, network optimization and
parallel computing. He has published in a variety of journals, including Operations
Research, Transportation Science, Computational Optimization and Applications,
Optimization Methods & Software, Journal of Optimization Theory and Applica-
tions, Optimization and Parallel Computing. He is also a member of the Scienti¬c


Committee of the Italian Center of Excellence on High Performance Computing, and
an editorial board member of Computers & Operations Research.


Introducing Logistics Systems

1.1 Introduction
Logistics deals with the planning and control of material ¬‚ows and related information
in organizations, both in the public and private sectors. Broadly speaking, its mission
is to get the right materials to the right place at the right time, while optimizing a
given performance measure (e.g. minimizing total operating costs) and satisfying a
given set of constraints (e.g. a budget constraint). In the military context, logistics is
concerned with the supply of troops with food, armaments, ammunitions and spare
parts, as well as the transport of troops themselves. In civil organizations, logistics
issues are encountered in ¬rms producing and distributing physical goods. The key
issue is to decide how and when raw materials, semi-¬nished and ¬nished goods
should be acquired, moved and stored. Logistics problems also arise in ¬rms and
public organizations producing services. This is the case of garbage collection, mail
delivery, public utilities and after-sales service.

Signi¬cance of logistics. Logistics is one of the most important activities in modern
societies. A few ¬gures can be used to illustrate this assertion. It has been estimated
that the total logistics cost incurred by USA organizations in 1997 was 862 billion
dollars, corresponding to approximately 11% of the USA Gross Domestic Product
(GDP). This cost is higher than the combined annual USA government expenditure in
social security, health services and defence. These ¬gures are similar to those observed
for the other North America Free Trade Agreement (NAFTA) countries and for the
European Union (EU) countries. Furthermore, logistics costs represent a signi¬cant
part of a company™s sales, as shown in Table 1.1 for EU ¬rms in 1993.

Logistics systems. A logistics system is made up of a set of facilities linked by
transportation services. Facilities are sites where materials are processed, e.g. manu-
factured, stored, sorted, sold or consumed. They include manufacturing and assembly
centres, warehouses, distribution centres (DCs), transshipment points, transportation
terminals, retail outlets, mail sorting centres, garbage incinerators, dump sites, etc.

Introduction to Logistics Systems Planning and Control G. Ghiani, G. Laporte and R. Musmanno
© 2004 John Wiley & Sons, Ltd ISBN: 0-470-84916-9 (HB) 0-470-84917-7 (PB)


Table 1.1 Logistics costs (as a percentage of GDP) in EU countries
(T, transportation; W, warehousing; I, inventory; A, administration).

Sector T W I A Total

Food/beverage 3.7 2.2 2.8 1.7 10.4
Electronics 2.0 2.0 3.8 2.5 10.3
Chemical 3.8 2.3 2.6 1.5 10.2
Automotive 2.7 2.3 2.7 1.2 8.9
Pharmaceutical 2.2 2.0 2.5 2.1 8.8
Newspapers 4.7 3.0 3.6 2.1 13.4

Transportation services move materials between facilities using vehicles and equip-
ment such as trucks, tractors, trailers, crews, pallets, containers, cars and trains. A few
examples will help clarify these concepts.

ExxonMobil Chemical is one of the largest petrochemical companies in the world.
Its products include ole¬ns, aromatics, synthetic rubber, polyethylene, polypropylene
and oriented polypropylene packaging ¬lms. The company operates its 54 manufac-
turing plants in more than 20 countries and markets its products in more than 130
The plant located in Brindisi (Italy) is devoted to the manufacturing of oriented
polypropylene packaging ¬lms for the European market. Films manufactured in Brin-
disi that need to be metallized are sent to third-party plants located in Italy and in
Luxembourg, where a very thin coating of aluminium is applied to one side. As a
rule, Italian end-users are supplied directly by the Brindisi plant while customers
and third-party plants outside Italy are replenished through the DC located in Milan
(Italy). In particular, this warehouse supplies three DCs located in Herstal, Athus and
Zeebrugge (Belgium), which in turn replenish customers situated in Eastern Europe,
Central Europe and Great Britain, respectively. Further details on the ExxonMobil
supply chain can be found in Section 8.2.

The P¬zer Pharmaceuticals Group is the largest pharmaceutical corporation in the
world. The company manufactures and distributes a broad assortment of pharmaceu-
tical products meeting essential medical needs, a wide range of consumer products for
self-care and well-being, and health products for livestock and pets. The P¬zer logis-
tics system comprises 58 manufacturing sites in ¬ve continents producing medicines
for more than 150 countries. Because manufacturing pharmaceutical products requires
highly specialized and costly machines, each P¬zer plant produces a large amount of
a limited number of pharmaceutical ingredients or medicines for an international mar-
ket. For example, ALFA10, a cardiovascular product, is produced in a unique plant for


an international market including 90 countries. For this reason, freight transportation
plays a key role in the P¬zer supply chain. A more detailed description of the P¬zer
logistics system is given in Section 8.3.

Railion is an international carrier, based in Mainz (Germany), whose core business
is rail transport. Railion transports a vast range of products, such as steel, coal, iron
ore, paper, timber, cars, washing machines, computers as well as chemical products. In
2001 the company moved about 500 000 containers. Besides offering high-quality rail
transport, Railion is also engaged in the development of integrated logistics systems.
This involves close cooperation with third parties, such as road haulage, waterborne
transport, forwarding and transshipment companies. More details on the freight rail
transportation system at Railion can be found in Section 8.4.

The Gioia Tauro marine terminal is the largest container transshipment hub on the
Mediterranean Sea and one of the largest in the world. In 1999, its traf¬c amounted to
2253 million Twenty-foot Equivalent Units (TEUs). The terminal is linked to nearly
50 end-of-line ports on the Mediterranean Sea. Inside the terminal is a railway station
where cars can be loaded or unloaded and convoys can be formed. Section 8.5 is
devoted to an in-depth description of the Gioia Tauro terminal.

The waste management system of the regional municipality of Hamilton-Went-
worth (Canada) is divided into two major subsystems: the solid waste collection
system and the regional disposal system. Each city or town is in charge of its own
kerbside garbage collection, using either its own workforce or a contracted service.
On the other hand, the regional municipality is responsible for the treatment and
disposal of the collected wastes. For the purposes of municipal solid waste planning,
the region is divided into 17 districts. The regional management is made up of a
waste-to-energy facility, a recycling facility, a 550 acre land¬ll, a hazardous waste
depot and three transfer stations. Section 8.6 contains a more detailed description of
this logistics system.

Supply chains. A supply chain is a complex logistics system in which raw materials
are converted into ¬nished products and then distributed to the ¬nal users (consumers
or companies). It includes suppliers, manufacturing centres, warehouses, DCs and
retail outlets. Figure 1.1 shows a typical supply chain in which the production and
distribution systems are made up of two stages each. In the production system, com-
ponents and semi-¬nished parts are produced in two manufacturing centres while
¬nished goods are assembled at a different plant. The distribution system consists


plant ...

Supplier CDC

Figure 1.1 A supply chain.

of two central distribution centres (CDCs) supplied directly by the assembly cen-
tre, which in turn replenish two regional distribution centres (RDCs) each. Of course,
depending on product and demand characteristics it may be more appropriate to design
a supply chain without separate manufacturing and assembly centres (or even without
an assembly phase), without RDCs or with different kinds of facilities (e.g. cross-
docks, see Section 1.2.2). Each of the transportation links in Figure 1.1 could be
a simple transportation line (e.g. a truck line) or of a more complex transportation
process involving additional facilities (e.g. port terminals) and companies (e.g. truck
carriers). Similarly, each facility in Figure 1.1 comprises several devices and subsys-
tems. For example, manufacturing plants contain machines, buffers, belt conveyors or
other material handling equipment, while DCs include shelves, forklifts or automatic
storage and retrieval systems. Logistics is not normally associated with the detailed
planning of material ¬‚ows inside manufacturing and assembly plants. Strictly speak-
ing, topics like aggregate production planning and machine scheduling are beyond
the scope of logistics and are not examined in this textbook. The core logistics issues
described in this book are the design and operations of DCs and transportation termi-

Push versus pull supply chains. Supply chains are often classi¬ed as push or pull
systems. In a pull (or make-to-order (MTO)) system, ¬nished products are manu-
factured only when customers require them. Hence, in principle, no inventories are
needed at the manufacturer. In a push (or make-to-stock (MTS)) system, production
and distribution decisions are based on forecasts. As a result, production anticipates
effective demand, and inventories are held in warehouses and at the retailers. Whether
a push system is more appropriate than a pull system depends on product features,
manufacturing process characteristics, as well as demand volume and variability.
MTO systems are more suitable whenever lead times are short, products are costly,
and demand is low and highly variable. In some cases, a mixed approach can be used.


For example, in make-to-assembly (MTA) systems components and semi-¬nished
products are manufactured in a push-based manner while the ¬nal assembly stage is
pull-based. Hence, the work-in-process inventory at the end of the ¬rst stage is used
to assemble the ¬nished product as demand arises. These parts are then assembled as
soon as customer orders are received.

Product and information ¬‚ows in a supply chain. Products ¬‚ow through the
supply chain from raw material sources to customers, except for obsolete, damaged
and nonfunctioning products which have to be returned to their sources for repair or
disposal. Information follows a reverse path. It traverses the supply chain backward
from customers to raw material suppliers. In an MTO system, end-user orders are
collected by salesmen and then transmitted to manufacturers who in turn order the
required components and semi-¬nished products from their suppliers. Similarly, in
an MTS system, past sales are used to forecast future product demand and associated
material requirements.
Product and information ¬‚ows cannot move instantaneously through the supply
channel. First, freight transportation between raw material sources, production plants
and consumption sites is usually time consuming. Second, manufacturing can take
a long time, not only because of processing itself, but also because of the limited
plant capacity (not all products in demand can be manufactured at once). Finally,
information can ¬‚ow slowly because order collection, transmission and processing
take time, or because retailers place their orders periodically (e.g. once a week), and
distributors make their replenishment decisions on a periodic basis (e.g. twice a week).

Degree of vertical integration and third-party logistics. According to a classical
economic concept, a supply chain is said to be vertically integrated if its components
(raw material sources, plants, transportation system, etc.) belong to a single ¬rm.
Fully vertically integrated systems are quite rare. More frequently the supply chain
is operated by several independent companies. This is the case of manufacturers
buying raw materials from outside suppliers, or using contractors to perform particular
services, such as container transportation and warehousing. The relationships between
the companies of a supply chain may be transaction based and function speci¬c (as
those illustrated in the previous example), or they can be strategic alliances. Strategic
alliances include third-party logistics (3PL) and vendor-managed resupply. 3PL is a
long-term commitment to use an outside company to perform all or part of a company™s
product distribution. It allows the company to focus on its core business while leaving
distribution to a logistics outsourcer. 3PL is suitable whenever the company is not
willing to invest much in transportation and warehousing infrastructures, or whenever
the company is unable to take advantage of economies of scale because of low demand.
On the other hand, 3PL causes the company to lose control of distribution and may
possibly generate higher logistics costs.

Retailer-managed versus vendor-managed resupply. Traditionally, customers
(both retailers or ¬nal consumers) have been in charge of monitoring their inventory


levels and place purchase orders to vendors (retailer-managed systems). In recent
years, there has been a growth in vendor-managed systems, in which vendors monitor
customer sales (or consumption) and inventories through electronic data interchange
(EDI), and decide when and how to replenish their customers. Vendors are thus able
to achieve cost savings through a better coordination of customer deliveries while
customers do not need to allocate costly resources to inventory management. Vendor-
managed resupply is popular in the gas and soft drink industries, although it is gaining
in popularity in other sectors. In some vendor-managed systems, the retailer owns the
goods sitting on the shelves, while in others the inventory belongs to the vendor. In
the ¬rst case, the retailer is billed only at the time where it makes a sale to a customer.

1.2 How Logistics Systems Work
Logistics systems are made up of three main activities: order processing, inventory
management and freight transportation.

1.2.1 Order processing
Order processing is strictly related to information ¬‚ows in the logistics system and
includes a number of operations. Customers may have to request the products by
¬lling out an order form. These orders are transmitted and checked. The availability
of the requested items and customer™s credit status are then veri¬ed. Later on, items
are retrieved from the stock (or produced), packed and delivered along with their
shipping documentation. Finally, customers have to be kept informed about the status
of their orders.
Traditionally, order processing has been a very time-consuming activity (up to
70% of the total order-cycle time). However, in recent years it has bene¬ted greatly
from advances in electronics and information technology. Bar code scanning allows
retailers to rapidly identify the required products and update inventory level records.
Laptop computers and modems allow salespeople to check in real time whether a
product is available in stock and to enter orders instantaneously. EDI allows companies
to enter orders for industrial goods directly in the seller™s computer without any

1.2.2 Inventory management
Inventory management is a key issue in logistics system planning and operations.
Inventories are stockpiles of goods waiting to be manufactured, transported or sold.
Typical examples are
• components and semi-¬nished products (work-in-process) waiting to be man-
ufactured or assembled in a plant;


• merchandise (raw material, components, ¬nished products) transported through
the supply chain (in-transit inventory);
• ¬nished products stocked in a DC prior to being sold;
• ¬nished products stored by end-users (consumers or industrial users) to satisfy
future needs.
There are several reasons why a logistician may wish to hold inventories in some
facilities of the supply chain.

Improving service level. Having a stock of ¬nished goods in warehouses close to
customers yields shorter lead times.
Reducing overall logistics cost. Freight transportation is characterized by econom-
ies of scale because of high ¬xed costs. As a result, rather than frequently delivering
small orders over long distances, a company may ¬nd it more convenient to satisfy
customer demand from local warehouses (replenished at low frequency).
Coping with randomness in customer demand and lead times. Inventories of
¬nished goods (safety stocks) help satisfy customer demand even if unexpected
peaks of demand or delivery delays occur (due, for example, to unfavourable
weather or traf¬c conditions).
Making seasonal items available throughout the year. Seasonal products can be
stored in warehouses at production time and sold in subsequent months.
Speculating on price patterns. Merchandise whose price varies greatly during the
year can be purchased when prices are low, then stored and ¬nally sold when prices
go up.
Overcoming inef¬ciencies in managing the logistics system. Inventories may be
used to overcome inef¬ciencies in managing the logistics system (e.g. a distri-
bution company may hold a stock because it is unable to coordinate supply and

Holding an inventory can, however, be very expensive for a number of reasons
(see Table 1.1). First, a company that keeps stocks incurs an opportunity (or capital)
cost represented by the return on investment the ¬rm would have realized if money
had been better invested. Second, warehousing costs must be incurred, whether the
warehouse is privately owned, leased or public (see Chapter 4 for a more detailed
analysis of inventory costs).
The aim of inventory management is to determine stock levels in order to minimize
total operating cost while satisfying customer service requirements. In practice, a good
inventory management policy should take into account ¬ve issues: (1) the relative
importance of customers; (2) the economic signi¬cance of the different products;
(3) transportation policies; (4) production process ¬‚exibility; (5) competitors™policies.


Plants Plants Plants

Warehouses Crossdocks

Retailers Retailers Retailers

(a) (b) (c)

Figure 1.2 Distribution strategies: (a) direct shipment; (b) warehousing; (c) crossdocking.

Inventory and transportation strategies. Inventory and transportation policies are
intertwined. When distributing a product, three main strategies can be used: direct
shipment, warehousing, crossdocking.
If a direct shipment strategy is used, goods are shipped directly from the manufac-
turer to the end-user (the retailers in the case of retail goods) (see Figure 1.2a). Direct
shipments eliminate the expenses of operating a DC and reduce lead times. On the
other hand, if a typical customer shipment size is small and customers are dispersed
over a wide geographic area, a large ¬‚eet of small trucks may be required. As a result,
direct shipment is common when fully loaded trucks are required by customers or
when perishable goods have to be delivered timely.
Warehousing is a traditional approach in which goods are received by warehouses
and stored in tanks, pallet racks or on shelves (see Figure 1.2b). When an order arrives,
items are retrieved, packed and shipped to the customer. Warehousing consists of four
major functions: reception of the incoming goods, storage, order picking and shipping.
Out of these four functions, storage and order picking are the most expensive because
of inventory holding costs and labour costs, respectively.
Crossdocking (also referred to as just-in-time distribution) is a relatively new
logistics technique that has been successfully applied by several retail chains (see
Figure 1.2c). A crossdock is a transshipment facility in which incoming shipments
(possibly originating from several manufacturers) are sorted, consolidated with other
products and transferred directly to outgoing trailers without intermediate storage or
order picking. As a result, shipments spend just a few hours at the facility. In pre-
distribution crossdocking, goods are assigned to a retail outlet before the shipment
leaves the vendor. In post-distribution crossdocking, the crossdock itself allocates
goods to the retail outlets. In order to work properly, crossdocking requires high
volume and low variability of demand (otherwise it is dif¬cult to match supply and
demand) as well as easy-to-handle products. Moreover, a suitable information system
is needed to coordinate inbound and outbound ¬‚ows.


Centralized versus decentralized warehousing. If a warehousing strategy is used,
one has to decide whether to select a centralized or a decentralized system. In central-
ized warehousing, a single warehouse serves the whole market, while in decentralized
warehousing the market is divided into different zones, each of which is served by
a different (smaller) warehouse. Decentralized warehousing leads to reduced lead
times since warehouses are much closer to customers. On the other hand, centralized
warehousing is characterized by lower facility costs because of larger economies of
scale. In addition, if customers™ demands are uncorrelated, the aggregate safety stock
required by a centralized system is signi¬cantly smaller than the sum of the safety
stocks in a decentralized system. This phenomenon (known as risk pooling) can be
explained qualitatively as follows: under the above hypotheses, if the demand from a
customer zone is higher than the average, then there will probably be a customer zone
whose demand is below average. Hence, demand originally allocated to a zone can
be reallocated to the other and, as a result, lower safety stocks are required. A more
quantitative explanation of risk pooling will be given in Section 2.2. Finally, inbound
transportation costs (the costs of shipping the goods from manufacturing plants to
warehouses) are lower in a centralized system while outbound transportation costs
(the costs of delivering the goods from the warehouses to the customers) are lower in
a decentralized system.

1.2.3 Freight transportation
Freight transportation plays a key role in today™s economies as it allows production
and consumption to take place at locations that are several hundreds or thousands
of kilometres away from each other. As a result, markets are wider, thus stimulating
direct competition among manufacturers from different countries and encouraging
companies to exploit economies of scale. Moreover, companies in developed countries
can take advantage of lower manufacturing wages in developing countries. Finally,
perishable goods can be made available in the worldwide market.
Freight transportation often accounts for even two-thirds of the total logistics cost
(see Table 1.1) and has a major impact on the level of customer service. It is there-
fore not surprising that transportation planning plays a key role in logistics system
A manufacturer or a distributor can choose among three alternatives to transport its
materials. First, the company may operate a private ¬‚eet of owned or rented vehicles
(private transportation). Second, a carrier may be in charge of transporting materials
through direct shipments regulated by a contract (contract transportation). Third,
the company can resort to a carrier that uses common resources (vehicles, crews,
terminals) to ful¬l several client transportation needs (common transportation).
In the remainder of this section, we will illustrate the main features of freight
transportation from a logistician™s perspective. A more detailed analysis is provided
in Chapters 6 and 7.

Manufacturer Agent or Wholesaler Retailer User
Channel 1

Channel 2

Channel 3

Channel 4

Channel 5

Channel 6

Channel 7

Figure 1.3 Channels of distribution.

Distribution channels. Bringing products to end-users or into retail stores may be
a complex process. While a few manufacturing ¬rms sell their own products to end-
users directly, in most cases intermediaries participate in product distribution. These
can be sales agents or brokers, who act for the manufacturer, or wholesalers, who
purchase products from manufacturers and resell them to retailers, who in turn sell
them to end-users. Intermediaries add a markup to the cost of a product but on the
whole they bene¬t consumers because they provide lower transportation unit costs
than manufacturers would be able to achieve. A distribution channel is a path followed
by a product from the manufacturer to the end-user. A relevant marketing decision
is to select an appropriate combination of distribution channels for each product.
Figure 1.3 illustrates the main distribution channels. Channels 1“4 correspond to
consumer goods while channels 5“7 correspond to industrial goods. In channel 1, there
are no intermediaries. This approach is suitable for a restricted number of products
(cosmetics and encyclopaedias sold door-to-door, handicraft sold at local ¬‚ea markets,
etc.). In channel 2, producers distribute their products through retailers (e.g. in the tyre
industry). Channel 3 is popular whenever manufacturers distribute their products only
in large quantities and retailers cannot afford to purchase large quantities of goods
(e.g. in the food industry). Channel 4 is similar to channel 3 except that manufacturers
are represented by sales agents or brokers (e.g. in the clothing industry). Channel 5 is
used for most industrial goods (raw material, equipment, etc.). Goods are sold in large
quantities so that wholesalers are useless. Channel 6 is the same as channel 5, except
that manufacturers are represented by sales agents or brokers. Finally, channel 7 is
used for small accessories (paper clips, etc.).

Freight consolidation. A common way to achieve considerable logistics cost sav-
ings is to take advantage of economies of scale in transportation by consolidating
small shipments into larger ones. Consolidation can be achieved in three ways. First,
small shipments that have to be transported over long distances may be consolidated


Table 1.2 Main features of the most common containers used for transporting solid goods.

Size Tare Capacity Capacity
(m3 ) (m3 )
Type (kg) (kg)

5.899 — 2.352 — 2.388
ISO 20 2300 21 700 33.13
12.069 — 2.373 — 2.405
ISO 40 3850 26 630 67.80

so as to transport large shipments over long distances and small shipments over short
distances (facility consolidation). Second, less-than-truckload pick-up and deliveries
associated with different locations may be served by the same vehicle on a multi-stop
route (multi-stop consolidation). Third, shipment schedules may be adjusted forward
or backward so as to make a single large shipment rather than several small ones
(temporal consolidation).

Modes of transportation. Transportation services come in a large number of vari-
ants. There are ¬ve basic modes (ship, rail, truck, air and pipeline), which can be
combined in several ways in order to obtain door-to-door services such as those pro-
vided, for example, by intermodal carriers and small shipment carriers.
Merchandise is often consolidated into pallets or containers in order to protect it and
facilitate handling at terminals. Common pallet sizes are 100—120 cm2 , 80—100 cm2 ,
90—110 cm2 and 120—120 cm2 . Containers may be refrigerated, ventilated, closed or
with upper openings, etc. Containers for transporting liquids have capacities between
14 000 and 20 000 l. The features of the most common containers for transporting
solid goods are given in Table 1.2.
When selecting a carrier, a shipper must take two fundamental parameters into
account: price (or cost) and transit time.
The cost of a shipper™s operated transportation service is the sum of all costs asso-
ciated with operating terminals and vehicles. The price of a transportation service is
simply the rate charged by the carrier to the shipper. A more detailed analysis of such
costs is reported in Chapters 6 and 7. Air is the most expensive mode of transportation,
followed by truck, rail, pipeline and ship. According to recent surveys, transportation
by truck is approximately seven times more expensive than by train, which is four
times more costly than by ship.
Transit time is the time a shipment takes to move between its origin to its destination.
It is a random variable in¬‚uenced by weather and traf¬c conditions. A comparison
between the average transit times of the ¬ve basic modes is provided in Figure 1.4.
One must bear in mind that some modes (e.g. air) have to be used jointly with other
modes (e.g. truck) to provide door-to-door transportation. The standard deviation and
the coef¬cient of variation (standard deviation over average transit time) of the transit
time are two measures of the reliability of a transportation service (see Table 1.3).

Rail. Rail transportation is inexpensive (especially for long-distance movements),
relatively slow and quite unreliable. As a result, the railroad is a slow mover of raw

Transit time


LTL trucking

TL trucking


0 750 1500 2250 3000 3500

Figure 1.4 Average transit time (in days) as a function of distance (in kilometres)
between origin and destination.

Table 1.3 Reliability of the ¬ve basic modes of transportation expressed by the standard
deviation and the coef¬cient of variation of the transit time.

Ranking Standard deviation Coef¬cient of variation

1 Pipeline Pipeline
2 Airplane Airplane
3 Truck Train
4 Train Truck
5 Ship Ship

materials (coal, chemicals, etc.) and of low-value ¬nished products (paper, tinned
food, etc.). This is due mainly to three reasons:
• convoys transporting freight have low priority compared to trains transporting
• direct train connections are quite rare;
• a convoy must include tens of cars in order to be worth operating.

Truck. Trucks are used mainly for moving semi-¬nished and ¬nished products.
Road transportation can be truckload (TL) or less-than-truckload (LTL). A TL ser-
vice moves a full load directly from its origin to its destination in a single trip (see
Figure 1.5). If shipments add up to much less than the vehicle capacity (LTL loads), it
is more convenient to resort to several trucking services in conjunction with consol-
idation terminals rather than use direct shipments (see Figure 1.6). As a result, LTL
trucking is slower than TL trucking.

Air. Air transportation is often used along with road transportation in order to pro-
vide door-to-door services. While air transportation is in principle very fast, it is

(California, USA)

(Arizona, USA)

Figure 1.5 Example of TL transportation.

(Nevada, USA)
(California, USA)

Line E
Line C

(California, USA)
Line B

Palm Springs
(California, USA)
Line D
Line A

San Diego
(California, USA) Phoenix
(Arizona, USA)

Figure 1.6 Example of LTL transportation.

slowed down in practice by freight handling at airports. Consequently, air transporta-
tion is not competitive for short and medium haul shipments. In contrast, it is quite
popular for the transportation of high-value products over long distances.

Intermodal transportation. Using more than one mode of transportation can lead
to transportation services having a reasonable trade-off between cost and transit time.
Although there are in principle several combinations of the ¬ve basic modes of trans-
portation, in practice only a few of them turn out to be convenient. The most frequent
intermodal services are air“truck (birdyback) transportation, train“truck (piggyback)
transportation, ship“truck (¬shyback) transportation. Containers are the most com-
mon load units in intermodal transportation and can be moved in two ways:
• containers are loaded on a truck and the truck is then loaded onto a train, a ship
or an airplane (trailer on ¬‚atcar);


• containers are loaded directly on a train, a ship or an airplane (container on

1.3 Logistics Managerial Issues
When devising a logistics strategy, managers aim at achieving a suitable compromise
between three main objectives: capital reduction, cost reduction and service level

Capital reduction. The ¬rst objective is to reduce as much as possible the level of
investment in the logistics system (which depends on owned equipment and invento-
ries). This can be accomplished in a number of ways, for example, by choosing public
warehouses instead of privately owned warehouses, and by using common carriers
instead of privately owned vehicles. Of course, capital reduction usually comes at the
expense of higher operating costs.

Cost reduction. The second objective is to minimize the total cost associated with
transportation and storage. For example, one can operate privately owned warehouses
and vehicles (provided that sales volume is large enough).

Service level improvement. The level of logistics service greatly in¬‚uences cus-
tomer satisfaction which in turn has a major impact on revenues. Thus, improving the
logistics service level may increase revenues, especially in markets with homogeneous
low-price products where competition is not based on product features.
The level of logistics service is often expressed through the order-cycle time, de¬ned
as the elapsed time between the instant a purchase order (or a service request) is issued
and the time goods are received by the customer (or service is provided to the user). The
order-cycle time is a random variable with a multinomial probability distribution. To
illustrate, the probability density function of the supply chain of Figure 1.1 is depicted
in Figure 1.7. When a retailer outlet issues an order, the following events may occur:

. 1
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