Optimization Modeling For Supply Chain Applications

✍ Scribed by Haitao Li

• Publisher: WSPC
• Year: 2023
• Tongue: English
• Leaves: 469
• Category: Library

✦ Synopsis

How to design an efficient and cost-effective logistics network? How to plan procurement, production, and transportation to meet customer demand with minimum operating costs? How to sequence jobs through machines for on-time order completion? And how to dispatch vehicles and schedule their routes to serve customers efficiently? Answers to these questions are key to effective and efficient supply chain operations. This book provides a systematic and comprehensive coverage of data-driven optimization modeling techniques and their applications in supply chain management. From the methodological perspective, it introduces various model building techniques including mathematical programming (linear and integer programming), network optimization, and constraint programming. From the application perspective, it covers the topics of supply chain network design, production planning, supply chain configuration, machine scheduling, and vehicle routing, among others. It also introduces the state-of-the-art optimization modeling software, the CPLEX OPL Studio, as a powerful and accessible tool for implementing the modeling techniques and solution methods in this book. Sample codes will be available upon purchase of the book. This book is essential reading material for researchers and students in business, data analytics, industrial engineering, computer science and applied math who would like to learn optimization modeling in the context of supply chains. It is also suitable for practitioners and consultants in industry who would like to understand the behind-the-scene techniques in off-the-shelf commercial optimization software. As a textbook, it can be used for an advanced undergraduate or graduate course in supply chain management, operations management, data analytics, economics, and industrial engineering.

✦ Table of Contents

Contents
Preface
About the Author
List of Figures
List of Tables
Part I Modeling Methodologies
Chapter 1. Introduction and Overview
1.1 Introduction to Optimization Modeling
1.2 Optimization Using Mathematical Programming
1.3 Optimization Applications in Supply Chains
1.4 Additional Notes
Exercises
Chapter 2. Linear Programming
2.1 Introduction to Linear Programming
2.2 Steps to Formulate an LP Model
2.3 A Generic LP Formulation
2.4 Algebraic Formulation for Math Programming Models
2.5 More LP Formulation Examples
2.5.1 Advertising-Mix Problem
2.5.2 Diet Problem
2.5.3 Transportation Problem
2.5.4 Personnel Scheduling
2.6 Additional Notes
Exercises
Chapter 3. Integer Programming
3.1 The Use of Integer Decision Variables
3.2 Some Classical Combinatorial Optimization Problems
3.2.1 Knapsack Problem
3.2.2 Set Covering Problem
3.2.3 Set Packing Problem
3.2.4 Set Partitioning Problem
3.2.5 Generalized Assignment Problem
3.2.6 Bin Packing Problem
3.3 Additional Notes
Exercises
Chapter 4. Network Optimization
4.1 Introduction to Network Optimization
4.2 Modeling a Pure Network
4.2.1 Modeling Input and Output
4.2.2 Modeling Connecting Activities
4.2.3 Modeling Objective Function
4.2.4 Modeling Flow Conservation
4.3 Minimum Cost Flow Problem
4.4 Generic LP Formulation for NETFORM
4.5 Special Cases of Minimum Cost Flow Problem
4.5.1 Transportation Problem
4.5.2 Transshipment Problem
4.5.3 Shortest Path Problem
4.5.4 Maximum Flow Problem
4.5.5 Assignment Problem
4.6 Modeling Complex Networks
4.7 Dynamic NETFORM Models
4.8 Generalized Network Models
4.9 Additional Notes
Exercises
Chapter 5. Quadratic Unconstrained Binary Optimization (QUBO) Modeling
5.1 Introduction to QUBO
5.2 Building QUBO Formulations
5.2.1 Principle of Reformulation
5.2.2 Reformulation of Constraints with Known Penalties
5.2.3 Reformulation of General BIPs
5.3 QUBO for Supply Chain Applications
5.3.1 Shortest Path Problem
5.3.2 Uncapacitated FLP
5.3.3 Job Assignment Problem
5.3.4 Crew Scheduling Problem
5.4 Additional Notes
Exercises
Chapter 6. Constraint Programming
6.1 Introduction to Constraint Programming
6.2 CP for Constraint Satisfaction Problems
6.3 CP for Scheduling Problems
6.3.1 Just-In-Time Scheduling
6.3.2 Job Shop Scheduling
6.3.3 Resource-Constrained Project Scheduling
6.4 Additional Notes
Exercises
Part II Supply Chain Applications
Chapter 7. Supply Chain Network Design
7.1 Introduction and Overview
7.2 Facility Location Problems
7.2.1 p-Median Problem
7.2.2 Uncapacitated Facility Location Problem
7.2.3 Capacitated Facility Location Problem
7.2.4 CFLP with Multiple-Sourcing
7.2.5 Multi-Commodity Facility Location Problem
7.3 Fixed-Charge Network Design
7.4 Multi-Modal Network Design
7.5 Dynamic Network Design
7.5.1 FLP with Time-Spatial Network
7.5.2 FCNFP with Time-Spatial Network
7.6 Hub Location Problems
7.6.1 p-Hub Median Problem
7.6.2 Multiple-Allocation p-Hub Median Problem
7.6.3 Uncapacitated Hub Location Problem
7.7 Additional Notes
Exercises
Chapter 8. Production Planning
8.1 Introduction and Overview
8.2 The Basic Production Planning Problem
8.3 Master Production Scheduling
8.4 Material Requirement Planning
8.5 Manufacturing Resource Planning (MRP II)
8.6 Additional Notes
Exercises
Chapter 9. Resource Planning
9.1 Introduction and Overview
9.2 Labor Strategy Optimization
9.3 Project Portfolio Optimization
9.4 Resource Matching and Assignment
9.5 Multi-Period Resource Assignment
9.6 Additional Notes
Exercises
Chapter 10. Supply Chain Configuration
10.1 Introduction and Overview
10.2 Safety Stock Placement Problem
10.3 The Basic Supply Chain Configuration Problem
10.4 Food Supply Chain Configuration
10.4.1 Food Loss
10.4.2 Food Quality
10.5 SCCP with Resource Constraints
10.6 Integrated SCCP with New Product Diffusion
10.7 Additional Notes
Exercises
Chapter 11. Machine Scheduling
11.1 Introduction and Overview
11.2 Single-Machine Scheduling
11.2.1 The Disjunctive Formulation
11.2.2 Position Based Formulation
11.2.3 Linear Ordering Formulation
11.3 Parallel Machine Scheduling
11.3.1 Position-Based Formulation
11.3.2 Linear Ordering Formulation
11.3.3 Time-Indexed Formulation
11.3.4 Routing-Based Formulation
11.4 Shop Scheduling
11.4.1 Flow Shop Scheduling Problem
11.4.1.1 Disjunctive Formulation
11.4.1.2 Position-Based Formulation
11.4.2 Job Shop Scheduling Problem
11.4.2.1 Disjunctive Formulation
11.4.2.2 Time-Indexed Formulation
11.4.3 Flexible Flow Shop Scheduling Problem
11.4.4 Flexible Job Shop Scheduling Problem
11.5 Additional Notes
Exercises
Chapter 12. Resource-Constrained Project Scheduling
12.1 Introduction and Overview
12.2 The Family of RCPSPs
12.3 Time-Cost Tradeoff Problems
12.3.1 Linear TCTP
12.3.2 Discrete TCTP
12.4 Single-Mode RCPSP
12.4.1 Time-Indexed Formulation
12.4.2 Disjunctive Formulation
12.4.3 Special cases of single-mode RCPSP
12.5 Multi-Mode RCPSP
12.6 RCPSP for MTO Supply Chain Configuration
12.6.1 Sourcing and Purchasing
12.6.2 Production Modes
12.6.3 Resource Constraints
12.7 Project Scheduling with Multi-Purpose Resources
12.8 Additional Notes
Exercises
Chapter 13. Traveling Salesman Problem and Its Variants
13.1 Introduction and Overview
13.2 Model Formulations of the TSP
13.2.1 Subtour Elimination Formulation
13.2.2 MTZ Formulation
13.2.3 Network Flow Based Formulation
13.3 TSP with Time Windows
13.4 The Black-and-White TSP
13.5 Additional Notes
Exercises
Chapter 14. Vehicle Routing Problem and Its Variants
14.1 Introduction and Overview
14.2 Formulations of the Capacitated VRP
14.2.1 The Compact Formulation
14.2.2 The MTZ Formulation
14.2.3 The Network Flow Based Formulation
14.3 VRP with Time Windows
14.4 VRP with Pickup-Delivery and Time Windows
14.5 Periodic VRP
14.6 Technician Routing and Scheduling
14.7 Additional Notes
Exercises
Chapter 15. Credit Term Optimization
15.1 Introduction
15.2 The Basic Credit Term Optimization Problem
15.3 The Bilevel Credit Term Optimization Problem
15.4 Additional Notes
Exercises
Appendices
Appendix 1 CPLEX OPL Studio
A1.1 Introduction
A1.2 A Guided Tour of CPLEX OPL Studio
A1.2.1 OPL Project
A1.2.2 Viewing Optimization Solutions
A1.3 Basics of OPL Syntax
A1.3.1 Sets
A1.3.2 Parameters
A1.3.3 Decision Variables
A1.3.4 Objective Function
A1.3.5 Constraints
A1.4 Examples of Mathematical Programming Models
A1.4.1 Product Mix Problem
A1.4.2 Advertising Mix Problem
A1.4.3 Transportation Problem
A1.5 Examples of Network Optimization
A1.5.1 Minimum Cost Flow Problem
A1.5.2 Shortest Path Problem
A1.6 Examples of Constraint Programming Models
A1.6.1 Send More Money
A1.6.2 N-Queen Problem
A1.6.3 Magic Series
A1.6.4 Project Scheduling
A1.6.5 Job Shop Scheduling
A1.6.6 Resource-Constrained Project Scheduling
Appendix 2 Simplex Method for Linear Programming
A2.1 Graph Method for Two-Variable LP
A2.2 The Simplex Method
A2.3 Transformations to the Canonical Form
A2.3.1 Minimization Problem
A2.3.2 Converting the ≥ Constraint
A2.3.3 Converting the Right-hand-side Constant
Appendix 3 Exact Methods for Integer Programming
A3.1 Introduction
A3.2 Linear Programming Relaxation
A3.3 Branch-and-Bound Method
A3.4 Cutting-Plane Method
Appendix 4 A Primer in Constraint Programming Methods
A4.1 Overview of Constraint Programming Methods
A4.2 Constraint Propagation
A4.3 Search
Instructions for Downloadable Electronic Slides
References
Index