Modeling the supply chain

Title:

Personal Author:

Shapiro, Jeremy E

Publication Information:

Pacific Grove, CA. : Duxbury, 2001

ISBN:

9780534373634

Subject Term:

Material requirements planning -- Mathematical models

Materials management -- Mathematical models

Business logistics -- Mathematical models

Industrial procurement -- Mathematical models

Available:*

Library	Item Barcode	Call Number	Material Type	Item Category 1	Status
Searching... PSZ KL	30000005175777	TS161 S485 2001	Open Access Book	Book	Searching... Unknown
Searching... PSZ KL	30000005173285	TS161 S485 2001	Open Access Book	Book	Searching... Unknown
Searching... PSZ KL	33000000016101	TS161 S485 2001	Open Access Book	Book	Searching... Unknown

With an emphasis on modeling techniques, Jeremy Shapiro's MODELING THE SUPPLY CHAIN is the perfect tool for courses in supply-chain management or for professional managers who seek better analytical tools for managing their supply chains, information technologists who are responsible for developing and/or maintaining such tools, and consultants who conduct supply-chain studies using models. Shapiro examines in detail the roles of data, models, and modeling systems in helping companies improve the management of their supply chains. The focus is on optimization models based on linear and mixed integer programming. Shapiro clearly illustrates that when properly applied, these methodologies can create accurate and comprehensive models of great practical value. The book also shows how competitive advantage in supply chain management can be most fully realized by implementing and applying optimization modeling systems.

Author Notes

Jeremy Shapiro is professor of operations research and management in the Sloan School of Management at MIT.

Part 1 Introduction to Supply Chain Management	p. 1
1 Supply Chain Management, Integrated Planning, and Models	p. 3
1.1 Fundamentals of Supply Chain Management	p. 5
Supply Chain Networks	p. 6
Integrated Supply Chain Planning	p. 7
Objectives of Supply Chain Management	p. 8
1.2 Overview of Supply Chain Models and Modeling Systems	p. 10
1.3 Supply Chain Modeling Incorporates Concepts from Several Management Disciplines	p. 12
Strategy Formation and the Theory of the Firm	p. 13
Logistics, Production, and Inventory Management	p. 17
Management Accounting	p. 19
Demand Forecasting and Marketing Science	p. 20
Operations Research	p. 22
1.4 Innovations in Information Technology Require and Support Supply Chain Modeling	p. 23
1.5 Organizational Adaptation to Integrated Supply Chain Management and Modeling	p. 25
Notes	p. 26
References	p. 27
2 Information Technology	p. 29
2.1 Developments in Enterprise Resource Planning Systems and E-Commerce	p. 30
ERP Systems	p. 31
E-Commerce	p. 32
2.2 Comparison of Transactional IT and Analytical IT	p. 36
Time Frame Addressed	p. 37
Purpose	p. 37
Business Scope	p. 37
Nature of Databases	p. 38
Response Time for Queries	p. 39
Implications for Business Process Redesign	p. 40
2.3 Hierarchy of Supply Chain Systems	p. 40
Components of the Supply Chain System Hierarchy	p. 40
Frequency of Analysis, Cycle Times, and Run Times of Supply Chain Systems	p. 46
Communication Among Supply Chain Systems of Data and Decisions	p. 46
Balancing Centralized and Decentralized Decision Making	p. 53
2.4 Legacy Systems and Legacy Thinking	p. 53
2.5 Final Thoughts	p. 55
Exercises	p. 56
Notes	p. 57
References	p. 59
Part 2 Modeling and Solution Methods	p. 61
3 Fundamentals of Optimization Models: Linear Programming	p. 63
3.1 Linear Programming Modeling Examples	p. 64
Resource Allocation Model	p. 65
Infeasible and Unbounded Models	p. 69
Spreadsheet Optimization	p. 70
Multiperiod Resource Allocation Model	p. 72
Network Models	p. 78
3.2 Properties of Linear Programming Models	p. 84
Linearity	p. 85
Separability and Additivity	p. 89
Indivisibility and Continuity	p. 89
Single Objective Function	p. 90
Data Known with Certainty	p. 90
3.3 Interpreting an Optimal Linear Programming Solution	p. 91
Shadow Prices	p. 92
Reduced Cost Coefficients	p. 94
Dual Linear Programming Model	p. 96
Parametric and Sensitivity Analysis	p. 98
3.4 Multiple Objective Optimization	p. 101
3.5 Stochastic Programming	p. 104
Generalizations	p. 109
3.6 Final Thoughts	p. 109
Exercises	p. 110
Notes	p. 113
References	p. 114
Appendix 3.A The Simplex Method of Linear Programming	p. 115
4 Fundamentals of Optimization Models: Mixed Integer Programming	p. 125
4.1 Mixed Integer Programming Modeling Vignettes	p. 126
Fixed Costs	p. 127
Economies of Scale	p. 130
Production Changeovers	p. 131
Multiple Choice and Other Nonnumeric Constraints	p. 132
4.2 Distribution Center Location Models	p. 133
DC Location Model	p. 134
Generalizations	p. 138
4.3 Supply Chain Network Optimization Models	p. 139
Strategic Planning at Ajax	p. 139
Generalizations	p. 151
4.4 Designing and Implementing Optimization Modeling Systems for Strategic and Tactical Planning	p. 151
System Design	p. 152
System Implementation	p. 154
4.5 Optimization Software	p. 158
Optimizers	p. 159
Algebraic Modeling Language Development Kits	p. 161
Spreadsheet Optimizers	p. 163
4.6 Final Thoughts	p. 163
Exercises	p. 164
Notes	p. 166
References	p. 167
Appendix 4.A The Branch-and-Bound Method for Mixed Integer Programming	p. 169
5 Unified Optimization Methodology for Operational Planning Problems	p. 177
5.1 Heuristic Methods for Combinatorial Optimization Problems	p. 179
Local Delivery Heuristics	p. 180
5.2 Overview of the Unified Optimization Methodology	p. 188
Production Scheduling Example of Decomposition	p. 189
Unified Optimization Methodology	p. 193
5.3 Unified Optimization Methodology Applied to Vehicle Routing	p. 197
Statements of the Optimization Models	p. 198
Numerical Solution	p. 202
Generalizations	p. 205
5.4 Unified Optimization Methodology Applied to Production Scheduling	p. 207
Company Background and Numerical Data	p. 207
Unified Optimization Methodology Specialized to Goodstone's Production Scheduling Problem	p. 209
Production Scheduling Solution	p. 213
Generalizations	p. 218
5.5 Final Thoughts	p. 218
Exercises	p. 219
Notes	p. 222
References	p. 223
6 Supply Chain Decision Databases	p. 225
6.1 Data Aggregations	p. 228
Aggregating Products	p. 229
Aggregating Customers and Markets	p. 231
Aggregating Suppliers	p. 232
6.2 Facility Data	p. 232
Recipes, Processes, Resources, and Costs	p. 232
6.3 Transportation Network Data	p. 237
Transportation Network Submodels	p. 237
Transportation Costs and Capacities	p. 240
Modal Choice and Shipment Sizes	p. 241
Utilities for Generating Networks	p. 242
6.4 Supplier Data	p. 242
Vendor Costs and Constraints	p. 243
6.5 Role of Management Accounting	p. 245
Develop Causal Cost Relationships of Direct and Indirect Costs	p. 247
Activity-Based Costing	p. 248
Connection of ABC to Optimization Models and the Taxonomy of Costs	p. 250
Computation of Transfer Prices, Product and Customer Costs from an Optimal Solution to a Supply Chain Model	p. 250
6.6 Demand Forecasting	p. 257
Background	p. 257
Types of Forecasting Models	p. 258
Demand Data Specifications for Optimization Models	p. 260
Forecasting Software	p. 261
6.7 Global and Policy Data	p. 261
6.8 Model Output Data	p. 262
Management Reports of Output Data	p. 263
Shadow Prices and Reduced Costs	p. 264
Derived Output	p. 265
6.9 Connections Among Supply Chain Decision Databases	p. 266
Scenarios	p. 267
Multiperiod Decision Databases	p. 268
Hierarchies	p. 269
6.10 Graphical Displays of Data Inputs and Outputs	p. 270
6.11 Final Thoughts	p. 271
Exercises	p. 273
Notes	p. 274
References	p. 275
Part 3 Applications	p. 277
7 Strategic and Tactical Supply Chain Planning: State-of-the-Art Modeling Applications	p. 279
7.1 Resources and the Resource-Based View of the Firm	p. 281
Taxonomy of Resources	p. 281
Summary of the Resource-Based View of the Firm	p. 282
Connections with Optimization Models	p. 283
7.2 Strategic Analysis of Logistics Supply Chains	p. 286
A Framework for Logistics Strategy Formation	p. 286
Constructing an Optimization Model for Strategic Logistics Planning	p. 289
7.3 Redesigning the Distribution Network of an Electronics Products Company	p. 292
7.4 Strategic Analysis of Manufacturing Supply Chains	p. 294
A Framework for Manufacturing Strategy Formation	p. 294
Constructing an Optimization Model for Strategic Manufacturing Planning	p. 298
7.5 Two Manufacturing Strategy Applications	p. 302
Worldwide Sourcing at Delta Industrial Chemicals	p. 303
Postmerger Consolidation of Consumer Paper Companies	p. 306
7.6 Tactical Planning	p. 310
7.7 Two Tactical Planning Applications	p. 312
Monthly Planning at an Industrial Gases Company	p. 312
Monthly Planning at a Beer Company	p. 315
7.8 Final Thoughts	p. 316
Exercises	p. 317
Notes	p. 319
References	p. 320
8 Strategic and Tactical Supply Chain Planning: Advanced Modeling Applications	p. 323
8.1 Integrating Supply Chain and Demand Management	p. 324
8.2 Price and Location Sensitive Revenue Curves	p. 326
8.3 Integrating Supply Chain and Marketing Models for Consumer Products	p. 330
Consumer Products Supply Chains	p. 331
Modeling the Effects of Marketing Decisions on Demand for Consumer Products	p. 333
Integrating Supply Chain and Marketing Models for Manufacturers of Consumer Products	p. 337
Illustrative Numerical Model	p. 340
8.4 Planning for New Product Introduction and Growth	p. 346
8.5 Optimization Models for Competitive Analysis	p. 349
Structural Analysis of Industries	p. 349
Theory of Industrial Organization	p. 351
A Model of Price Competition	p. 353
Illustrative Numerical Model	p. 355
8.6 Application of Competitive Analysis in the Forest Products Industry	p. 362
Practical Issues of Price Competition	p. 363
8.7 Decision Trees and Stochastic Programming	p. 364
Decision Trees	p. 366
An Inventory Example of Stochastic Programming	p. 370
8.8 Supply Chain Strategies for Managing Product Variety	p. 375
Exploit Component Commonality and Postponement of Product Differentiation	p. 376
Assemble Differentiated Products from Vanilla Boxes	p. 377
Implement Quick Response to Early Sales	p. 378
8.9 Scenario Planning	p. 382
Methodology	p. 382
Connections to Optimization Modeling	p. 384
8.10 Final Thoughts	p. 384
Exercises	p. 386
Notes	p. 387
References	p. 389
9 Integration of Financial and Physical Supply Chains	p. 391
9.1 Optimization Models for Corporate Financial Planning	p. 392
Modeling the Balance Sheet	p. 393
Numerical Example of an Optimization Model for Corporate Financial Planning	p. 395
Model and Methodological Extensions	p. 401
9.2 Financial Planning Issues Facing the Multinational Corporation	p. 402
9.3 A Network Illustration	p. 403
9.4 Financial Flows Model	p. 406
Statement of the Financial Flows Model	p. 408
Financial Flows Model Results	p. 412
9.5 Modeling Exchange Rate Risks	p. 415
9.6 Real Options for Hedging Risks in the Global Economy	p. 419
9.7 Final Thoughts	p. 421
Exercises	p. 422
Notes	p. 426
References	p. 427
10 Operational Supply Chain Planning	p. 429
10.1 Taxonomies of Operational Planning Problems	p. 430
Production Planning and Scheduling	p. 431
Vehicle Routing and Scheduling	p. 438
Human Resources Scheduling	p. 440
10.2 Modeling Systems for Operational Planning	p. 441
System Integration	p. 441
Steps to Follow in Using a System	p. 443
Real-Time Operational Planning	p. 446
Other Uses of a Modeling System	p. 447
Training, Learning, and System Evolution	p. 447
10.3 Vehicle Routing System for an E-Commerce Company	p. 448
Company Background	p. 449
Routing System Description and Use	p. 450
Driver Assignment	p. 455
10.4 Production Planning System for a Semiconductor Company	p. 455
Manufacturing and Marketing Background	p. 456
Planning and Modeling Approaches	p. 458
Implementation	p. 461
Results	p. 462
10.5 Simulation Models and Systems	p. 463
Deterministic Simulation	p. 463
Monte Carlo Simulation	p. 463
Simulation Software	p. 468
Simulation versus Optimization	p. 469
10.6 Final Thoughts	p. 470
Exercises	p. 471
Notes	p. 474
References	p. 475
11 Inventory Management	p. 477
11.1 Inventory Theory Models	p. 479
Deterministic Models	p. 479
Probabilistic Models	p. 481
ABC Classification	p. 485
11.2 Incorporating Inventory Management Decisions in Strategic and Tactical Supply Chain Models	p. 486
Incorporating Inventory Management Decisions in Strategic Supply Chain Models	p. 487
Incorporating Inventory Management Decisions in Tactical Supply Chain Models	p. 492
11.3 Inventory Management in Distribution Supply Chains	p. 495
Distribution Scheduling in a Reverse Logistics Company	p. 495
Multiechelon Spare Parts Distribution System at IBM	p. 500
11.4 Inventory Management in Manufacturing Supply Chains	p. 504
Optimizing Inventory across Hewlett-Packard's Printer Supply Chains	p. 504
Optimal Safety Stock Placement in Kodak's Manufacturing Supply Chains	p. 508
11.5 Final Thoughts	p. 512
Exercises	p. 514
Notes	p. 515
References	p. 516
Part 4 The Future	p. 517
12 Organizational Adaptation to Optimization Modeling Systems	p. 519
12.1 How Organizations Make Decisions	p. 521
The Theory of Rational Choice versus the Reality of Organizational Behavior	p. 522
Uncertainty and Risk	p. 524
Rule-Based Decision Making	p. 524
Deriving Meaning from the Decision Environment	p. 525
Decision-Making Ecologies	p. 526
12.2 Contested Issues about Organizational Decision Making	p. 527
Choice-Based versus Rule-Based Decision Making	p. 528
Clear versus Ambiguous Decision Making	p. 530
Instrumental versus Interpretive Decision Making	p. 535
Supply Chain Management as an Interacting Ecology	p. 538
12.3 Information Technology as Competitive Advantage	p. 539
Recent History of IT as Competitive Advantage	p. 539
Resource-Based Analysis	p. 540
Attributes of IT as Possible Sources of Competitive Advantage	p. 541
Complementary Organizational Resources	p. 544
12.4 Exploitative versus Exploratory IT Developments	p. 547
Acquisition or Development of a Modeling System	p. 548
Use of a Modeling System	p. 549
Enhancement of a Modeling System	p. 550
12.5 Business Process Redesign and IT	p. 550
Modeling Systems Invoke Business Process Redesign	p. 553
12.6 Supply Chain Coordination Processes and Incentive Contracts	p. 557
Selecting Coordination Processes	p. 558
Principal-Agent Theories of Incentives	p. 559
12.7 No Gain without Pain	p. 562
Stages of a Strategic Supply Chain Study	p. 563
Summary	p. 566
12.8 Outlook for the Future of Modeling Systems and Their Applications	p. 567
Exercises	p. 572
Notes	p. 573
References	p. 575
Index	p. 577
Credits	p. 583

Available:*

On Order

Summary

Summary

Author Notes

Table of Contents