作者：李鹏著
页数：181页
出版社：经济管理出版社
出版日期：2019
ISBN：9787509663059
电子书格式：pdf/epub/txt
内容简介
随着经济的全球化发展，供应链结构变得日益复杂，集成供应链管理已成为企业在满足客户要求的同时降低企业成本的重要策略之一，这种变化使得学术研究人员和行业从业者在过去二十年中越来越关注于多级库存管理。
作者简介
李鹏，女，1984年8月生，讲师，就职于西安理工大学经济与管理学院。2006年和2009年分别获得郑州大学管理学学士学位、西北工业大学管理学硕士学位，2009年赴法国特鲁瓦技术大学攻读博士学位，并于2013年获得系统安全与优化专业博士学位。研究方向包括多级库存优化、闭环供应链优化、系统优化与运筹学等。目前，已承担国家自然基金项目1项，发表学术论文10余篇。
本书特色
随着经济的全球化发展，供应链结构变得日益复杂，集成供应链管理已成为企业在满足客户要求的同时降低企业成本的重要策略之一，这种变化使得学术研究人员和行业从业者在过去二十年中越来越关注于多级库存管理。
目录
Chapter 1 Introduction
1.1 Inventory Management
1.2 Multi-Echelon Inventory Systems
1.3 Multi-Echelon Inventory Management
1.4 Models and Methods Used for Multi-Echelon Inventory Management
1.4.1 Inventory Models
1.4.2 Inventory Policies
1.4.3 Inventory Optimization Approaches
1.5 The Problems Studied in This Thesis
1.6 Literature Review of Multi-Echelon Inventory Management
1.6.1 General Studies of Multi-Echelon Inventory Management
1.6.2 Stochastic Service Approach for Serial Inventory Systems
1.6.3 Stochastic Service Approach for Assembly Inventory Systems
1.6.4 Stochastic Service Approach for Distribution Inventory Systems
1.6.5 Guaranteed Service Approach for Multi-Echelon Inventory Systems
1.6.6 Comparison of Stochastic-Service Approach and Guaranteed-Service Approach
1.7 The Contributions of the Thesis
1.8 Conclusion
Chapter 2 Preliminaries
2.1 Fundamentals
2.1.1 Network Structures
2.1.2 Demand Processes
2.2 Inventory Control
2.2.1 Inventory Accounting
2.2.2 Batch Ordering (R, Q) Policy
2.2.3 Performance Measures for Inventory Control
2.3 Guaranteed Service Approach
2.4 Operating Flexibility and GSA
2.5 Batch Ordering (R, Q) Policy and GSA
Chapter 3 Optimization of (R, Q) Policies for Serial Systems
3.1 Problem Description
3.1.1 Serial System Studied
3.1.2 Maximum Reasonable Lead Time Demand Level
3.1.3 Cost Structure
3.2 Mathematical Model Formulation
3.2.1 Definitions and Notations
3.2.2 Objective Function
3.2.3 Model Formulation
3.3 Dynamic Programming Algorithms for Q-problem…
3.3.1 Basic Principle of DP
3.3.2 Dynamic Programming Algorithm
3.4 Dynamic Programming Algorithm for R-problem
3.5 Optimization Procedure
3.5.1 The Calculation of the Fill Rate fl
3.5.2 Algorithm for Original Model P
3.6 Experiments Results
3.6.1 Experiments for the Resolution of Q-problem
3.6.2 Experiments for the Resolution of R-problem
3.6.3 Experiments for the Resolution of Problem P with a Given Service Level
3.6.4 Structural Analysis of the (R, Q) Policy Found by the GSA
3.7 Conclusion
Chapter 4 Optimization of (R, Q) Policies for Assembly Systems
4.1 Problem Description
4.2 Mathematical Model Formulation
4.3 Dynamic Programming Algorithm for Q-problem
4.3.1 Assumptions and Notations
4.3.2 State Space of Qi
4.3.3 State Space Reduction
4.3.4 Dynamic Programme Algorithm
4.4 Dynamic Programming Algorithm for R-problem
4.5 Optimization Procedure
4.6 Experiments Results
4.6.1 Experiments for the Resolution of Q-problem
4.6.2 Experiments for the Resolution of R-problem
4.6.3 Experiments for the Sensitivity Analysis for the Two Algorithms
4.6.4 Experiments for the Resolution of Problem P with a Given Service Level
4.7 Conclusions
Chapter 5 Optimization of (R, Q) Policies for Two-Level Distribution Systems
5.1 Problem Description
5.2 Mathematical Model Formulation
5.3 Dynamic Programming Algorithm for Q-problem
5.3.l Integer-ratio Constraints for Q-problem
5.3.2 Dynamic Programming for Q-problem
5.4 Dynamic Programming Algorithm for R-problem
5.5 Optimization Procedure
5.6 Numerical Experiments
5.6.1 Experiments for the Resolution of Q-problem
5.6.2 Experiments for the Resolution of R-problem
5.6.3 Experiments for the Resolution of Problem P with a Given Service Level
5.7 Conclusion
Chapter 6 Conclusions and Perspectives
Resume en Francais
References
1.1 Inventory Management
1.2 Multi-Echelon Inventory Systems
1.3 Multi-Echelon Inventory Management
1.4 Models and Methods Used for Multi-Echelon Inventory Management
1.4.1 Inventory Models
1.4.2 Inventory Policies
1.4.3 Inventory Optimization Approaches
1.5 The Problems Studied in This Thesis
1.6 Literature Review of Multi-Echelon Inventory Management
1.6.1 General Studies of Multi-Echelon Inventory Management
1.6.2 Stochastic Service Approach for Serial Inventory Systems
1.6.3 Stochastic Service Approach for Assembly Inventory Systems
1.6.4 Stochastic Service Approach for Distribution Inventory Systems
1.6.5 Guaranteed Service Approach for Multi-Echelon Inventory Systems
1.6.6 Comparison of Stochastic-Service Approach and Guaranteed-Service Approach
1.7 The Contributions of the Thesis
1.8 Conclusion
Chapter 2 Preliminaries
2.1 Fundamentals
2.1.1 Network Structures
2.1.2 Demand Processes
2.2 Inventory Control
2.2.1 Inventory Accounting
2.2.2 Batch Ordering (R, Q) Policy
2.2.3 Performance Measures for Inventory Control
2.3 Guaranteed Service Approach
2.4 Operating Flexibility and GSA
2.5 Batch Ordering (R, Q) Policy and GSA
Chapter 3 Optimization of (R, Q) Policies for Serial Systems
3.1 Problem Description
3.1.1 Serial System Studied
3.1.2 Maximum Reasonable Lead Time Demand Level
3.1.3 Cost Structure
3.2 Mathematical Model Formulation
3.2.1 Definitions and Notations
3.2.2 Objective Function
3.2.3 Model Formulation
3.3 Dynamic Programming Algorithms for Q-problem…
3.3.1 Basic Principle of DP
3.3.2 Dynamic Programming Algorithm
3.4 Dynamic Programming Algorithm for R-problem
3.5 Optimization Procedure
3.5.1 The Calculation of the Fill Rate fl
3.5.2 Algorithm for Original Model P
3.6 Experiments Results
3.6.1 Experiments for the Resolution of Q-problem
3.6.2 Experiments for the Resolution of R-problem
3.6.3 Experiments for the Resolution of Problem P with a Given Service Level
3.6.4 Structural Analysis of the (R, Q) Policy Found by the GSA
3.7 Conclusion
Chapter 4 Optimization of (R, Q) Policies for Assembly Systems
4.1 Problem Description
4.2 Mathematical Model Formulation
4.3 Dynamic Programming Algorithm for Q-problem
4.3.1 Assumptions and Notations
4.3.2 State Space of Qi
4.3.3 State Space Reduction
4.3.4 Dynamic Programme Algorithm
4.4 Dynamic Programming Algorithm for R-problem
4.5 Optimization Procedure
4.6 Experiments Results
4.6.1 Experiments for the Resolution of Q-problem
4.6.2 Experiments for the Resolution of R-problem
4.6.3 Experiments for the Sensitivity Analysis for the Two Algorithms
4.6.4 Experiments for the Resolution of Problem P with a Given Service Level
4.7 Conclusions
Chapter 5 Optimization of (R, Q) Policies for Two-Level Distribution Systems
5.1 Problem Description
5.2 Mathematical Model Formulation
5.3 Dynamic Programming Algorithm for Q-problem
5.3.l Integer-ratio Constraints for Q-problem
5.3.2 Dynamic Programming for Q-problem
5.4 Dynamic Programming Algorithm for R-problem
5.5 Optimization Procedure
5.6 Numerical Experiments
5.6.1 Experiments for the Resolution of Q-problem
5.6.2 Experiments for the Resolution of R-problem
5.6.3 Experiments for the Resolution of Problem P with a Given Service Level
5.7 Conclusion
Chapter 6 Conclusions and Perspectives
Resume en Francais
References
