Analysis and algorithms for service parts supply chains维修配件供应链用分析与算法 azw3 chm 地址 kindle 阿里云 下载 umd pdf

Services requiring parts has become a $1.5 trillion business annually worldwide，creating a tremendous incentive to manage the logistics of these parts efficiently by making planning and operational decisions in a rational and rigorous manner。This book provides a broad overview of modeling approaches and solution methodologies for addressing service parts inventory problems found in high-powered technology and aerospace applications。The focus in this work is on the management of high cost，low demand rate service parts found in multi-echelon settings。The text may be used in a variety of courses for first-year graduate students or senior undergraduates，as well as for practitioners，requiring only a background in stochastic processes and optimization。It will serve as an excellent reference for key mathematical concepts and a guide to modeling a variety of multi-echelon service parts planning and operational problems。

Preface

1 Introduction

1.1 Taxonomy of Service Parts Inventory Systems

1.1.1 The Items

1.1.2 Inventory Policies

1.2 An Overview ofthe Book

2 Background：Analysis of(s-1.S)and Order-Up-To Policies

2.1 0ptimality of Order—UP-Tolicies in a Single Location.

Periodic Review.BackorderEnvironment

2.2 Optimality Of Order—UP一T0 Policies in Serial Systems

2.2.1 The Single.Unit Single—Customer Approach： Single Location Case.

2.2.2 Stochastic Lcad Times

2.2.3 The Serial Systems Case

2.2.4 Continuous Review Systems

2.3 Problem Set.Chapter 2

3 Background Concepts：An Introduction to the（s-1，s）Policy underPoisson andCompoundPoissonDemand

3.1 Steady State Distribution of the Number of Units in ResupplY

3.1.1 Backorder Case.

3.1.2 Lost Sales Case.

3.1.3 Another Backorder Case：Delayed Customer Due Dates

3.2 Performance Measures.

3.3 Properties ofthe Performance Measures

3.4 Finding Stock Levels in(s—l，s)Policy Managed Systems： Optimization Problem Formulations and Solution Algorithms

　　3.4.1 Everett’S Theorem.

　　3.4.2 First Example：Minimize Expected Backorders Subject to an Inventory Investment Constraint.

　　3.4.3 Second Example：Maximize Expected System Average Fill Rate Subject to an Inventory Investment Constraint

3.5 Problem Set，Chapter 3

4 An Exact Model for a Depot.Base Two Echelon Inventory and

Repair System.

4.1 Introduction.

4.2 Model Development

4.3 Some Extensions.

4.4 Problem Set，Chapter 4

5 Tactical Planning Models for Managing Recoverable Items

5.1 The METRIC System.

5.1.1 System Operation and Definitions.

5.1.2 The Optimization Problem

5.2 Waiting Time Analysis

5.3 A Multi—Indenture System

5.3.1 A Two—Echelon，Two—Indenture Resupply System.

5.3.2 Calculating the Stationary Probability Distribution of the

Number of Units in Resupply

53.3 Computing Depot and Base Stock Levels for Each LRU

and SRU.

5.4 Problem Set，Chapter 5.

6 A Continuous Time。Multi.Echelon.Multi.Item

System with Time-Based Service Level Constraints

6.1 The Model

6.1.1 Modeling Assumptions

6.1.2 Service Level Requirements

6.1.3 Notation and Problem Statement

6.2 Channel Fill Rate Functions.

6.2.1 TheChannelFillRate

6.2.2 The Channel Fill Rate

6.2.3 The Channel Fill Rate

6.2.4 The Channel Fill Rate

6.2.5 The Distributions of Y1，Y2，Y3，and Fill Rate Accuracy

6.3 Solution Approach

6.3.1 Procedure Overview.

6.3.2 Master Problem for SLS.

6.3.3 Column Generation.

6.3.4 Constructing the Initial Vector Sets

6.4 Problem Set，Chapter 6

7 Lateral resupply and pooling in multi-echelon systems

8 Capacity-limited systems

9 Extension of palm's theorem to nonstationary demand processes

10 Real-time execution systems

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