Supply chain analytics

Table of content

Section I Overview of Logistics and Supply Chain Management

Chapter 1 Overview of Logistics and Supply Chain Management

1.1 Introduction

1.2 SCM and Competitive Advantage

1.3 Driving Forces in Business and SCM

1.4 Overview of Logistics Management

1.5 Overview of Supply Chain Management

1.6 Supply Chain Analytics



Section II Overview of Optimization Methods

Chapter 2 Overview of Optimization Methods

2.1 Introduction and Historical Perspective

2.2 Constrained Optimization Models

2.3 Assumptions of an LPP

2.4 General Form of LPP

2.5 Graphical Solution to Furniture Problem

2.6 Simplex Method

2.7 A Few Examples of Formulation of LPP

2.8 Transportation Problem

2.9 Assignment Problem



Section III Facilities Location and Warehousing Decisions

Chapter 3 Facility Locations and Discrete Location Models

3.1 Introduction

3.2 Single Facility Location Problems

3.3 Multiple Facility Location Problems

3.4 Mathematical Formulations of Popular Location Problems

3.5 Conclusion



Chapter 4 Facility Locations through Heuristic and Other Approaches

4.1 Introduction

4.2 Heuristic Methods

4.3 P-Median Solution for Example 4.1

4.4 Greedy Drop Heuristic for Capacitated Depots with Fixed Costs

4.5 Capacitated Fixed Charge Model Solution for Example 4.1

4.6 Mathematical Programming Approach to Facilities Location Problems

4.7 Baumol and Wolfe Method

4.8 Spatial Interaction Models



Chapter 5 Tactical and Operational Decisions in Warehousing

5.1 Introduction and Space Determination in Warehouse Planning

5.2 Warehouse Operations and Layout Decisions

5.3 Handling Decisions

5.4 Layout Configuration Decisions

Section IV Inventory Decisions

Chapter 6 Inventory Concepts, Costs and Basic Models

6.1 Introduction

6.2 Reasons for Keeping Inventory

6.3 Reasons against Keeping Inventory

6.4 ABC Analysis and Pareto Analysis (80-20 Rule)

6.5 Managing Inventories and Inventory-Carrying Costs

6.6 Single-Period Inventory Models (Newsvendor Model)

6.7 Optimal Stock Level in Newsvendor Models (for Continuous Distributions)

6.8 Repetitive Order Quantities (Pull Models)

6.9 Production Order Quantities (POQ) Models

6.10 Quantity Discount EOQ Models



Chapter 7 Inventory under Uncertainty and Service Levels

7.1 Introduction

7.2 Factors Affecting Safety Inventory

7.3 Understanding Demand Uncertainty

7.4 Service Levels and Product Availability Measures

7.5 Average Inventory Level

7.6 Estimation of Unit Service Level or Fill Rate

7.7 Impact of Lead Time Uncertainty on Inventory Decisions

7.8 Backorder Case

7.9 Lost Sales Case



Chapter 8 Joint Replenishment and Lot Sizing in Inventory Decisions

8.1 Introduction and Inventory Investment Decisions

8.2 Lot Sizing Inventory Management Interpolation Technique

8.3 Lagrangian Multipliers

8.4 Joint Replenishment of Multiple Items

8.5 Lot-Sizing Techniques (Dynamic Lot Sizing)

8.6 Multi-Echelon Inventory Decisions

8.7 Risk Pooling or Centralization of Inventories



Section V Transportation Decisions

V Transportation Decisions



Chapter 9 Trade-Off Decisions and Network Models in Transportation

9.1 Introduction

9.2 Basic Trade-Offs in Transport Decisions

9.3 Transport Service Selection

9.4 Operational Planning in Transportation

9.5 Network Models

9.6 Minimal Spanning Tree

9.7 Shortest Path Algorithms

9.8 Bellman–Ford Algorithm ( for Negative Link Lengths)

9.9 Floyd-Warshall Algorithm

9.10 Maximum Flow Model



Chapter 10 Routing Using the Traveling Salesman Problem Algorithms in Transportation

10.1 Introduction

10.2 Characteristics of Routing and Scheduling Problems

10.3 The Traveling Salesman Problem

10.4 Heuristics for Solving a TSP

10.5 Construction Heuristics

10.6 k-Opt Tour Improvement Method



Chapter 11 Routing and Scheduling Problems and Methods

11.1 Introduction

11.2 Vehicle Routing Problems

11.3 Branch and Bound Method for Solving Routing Problems

11.4 Clarke–Wright Savings Algorithm for Solving Routing Problems

11.5 Sweep Heuristic for Solving VRPs

11.6 Generalized Assignment Method

11.7 Vehicle Scheduling Methods

11.8 Deficit Function Approach to Vehicle Scheduling



Section VI Multicriteria Decision Making

Chapter 12 Multi-Criteria Decision Making

12.1 Introduction

12.2 Multiple-Attribute Utility Theory

12.3 Terminologies in MADM or MCDM Methods

12.4 Analytic Hierarchy Process

12.5 Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS)

12.6 Basics of Fuzzy Logic

12.7 Fuzzy Analytic Hierarchy Process

12.8 Fuzzy TOPSIS

Description
Supply Chain Analytics is a structured collation of important analytical tools and techniques that specifically addresses critical decision areas in warehousing, inventory, and transportation in supply chain management, which are mostly available in some technical academic papers and proceedings of conferences and so will be very helpful to find them all in one book. This book explains various practical application methods in a lucid manner so that any student with basic understanding of Decision Sciences will be able to understand popular analytical tools and techniques useful in supply chain management areas.