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Supply Chain Optimization, Design, and Management

Book Description

Supply Chain Optimization, Design, and Management: Advances and Intelligent Methods presents computational intelligence methods for addressing supply chain issues. Emphasis is given to techniques that provide effective solutions to complex supply chain problems and exhibit superior performance to other methods of operations research.

Table of Contents

  1. Cover
  2. Title Page
  3. Copyright Page
  4. Preface
    1. The Role of Quantitative Methods in Supply Chain Management
  5. Acknowledgment
  6. Chapter 1: Nature-Inspired Intelligence in Supply Chain Management
    1. Abstract
    2. INTRODUCTION
    3. SUPPLY CHAIN MANAGEMENT OPTIMIZATION PROBLEM
    4. NATURE-INSPIRED INTELLIGENCE: GENERAL FRAMEWORK AND CERTAIN TECHNIQUES
    5. ANT COLONY OPTIMIZATION (ACO) ALGORITHM
    6. PARTICLE SWARM OPTIMIZATION (PSO) ALGORITHM
    7. GENETIC ALGORITHMS (GA)
    8. GENETIC PROGRAMMING (GP)
    9. DNA COMPUTING
    10. ARTIFICIAL IMMUNE SYSTEMS (AIS)
    11. BASIC LITERATURE REVIEW AND FINDINGS
    12. APPLICATIONS OF ACO ALGORITHMS ON SUPPLY CHAIN MANAGEMENT PROBLEMS
    13. APPLICATIONS OF GA ALGORITHMS ON SUPPLY CHAIN MANAGEMENT PROBLEMS
    14. APPLICATIONS OF PSO ALGORITHMS ON SUPPLY CHAIN MANAGEMENT PROBLEMS
    15. APPLICATIONS OF OTHER NII TECHNIQUES ON SUPPLY CHAIN PROBLEMS
    16. CONCLUSION
  7. Section 1: Synthesis and Design of Supply Chain
    1. Chapter 2: Coalitional Added Services in a Linear Neutral e-Marketplace
      1. Abstract
      2. INTRODUCTION
      3. LITERATURE OVERVIEW
      4. RESEARCH CONTEXT
      5. Multi Agent Architecture
      6. Cooperative Game theory and Shapley approach
      7. Simulation environment
      8. Simulation results
      9. Summary and conclusion
    2. Chapter 3: Investing in Excess Capacity
      1. Abstract
      2. INTRODUCTION
      3. LITERATURE REVIEW
      4. RESEARCH CONTEXT
      5. NO INFORMATION SHARING MODEL (NIS)
      6. INFORMATION SHARING MODEL (IS)
      7. NEGOTIATION
      8. SIMULATION ENVIRONMENT
      9. RESULTS
      10. SUMMARY AND CONCLUSIONS
      11. APPENDIX
    3. Chapter 4: Optimal Design and Operation of Supply Chain Networks under Demand Uncertainty
      1. Abstract
      2. Introduction
      3. Representation of Uncertainty
      4. Mathematical framework
      5. Case study
      6. Conclusion
      7. Appendix
  8. Section 2: Planning in Large Supply Chains
    1. Chapter 5: A Computational Intelligence Approach to Supply Chain Demand Forecasting
      1. Abstract
      2. INTRODUCTION
      3. BACKGROUND
      4. ARTIFICIAL NEURAL NETWORKS
      5. THE OLMAM ALGORITHM
      6. SUPPORT VECTOR MACHINES
      7. INFORMATION SOURCES
      8. RESULTS
      9. CONCLUSION
    2. Chapter 6: Generating Supply Chain Ordering Policies using Quantum Inspired Genetic Algorithms and Grammatical Evolution
      1. Abstract
      2. Introduction
      3. Background
      4. Methodology & Implementation
      5. Discussion
      6. Conclusions and FuTURE rESEARCH dIRECTIONs
      7. Appendix: grammars used
    3. Chapter 7: Quantitative Risk Management Models for Newsvendor Supply Chains
      1. Abstract
      2. INTRODUCTION
      3. LITERATURE REVIEW AND TAXONOMY
      4. PROBLEMS AND SOLUTION METHODOLOGIES
      5. CONCLUSION AND FUTURE RESEARCH
    4. Chapter 8: Relief Distribution Networks
      1. Abstract
      2. INTRODUCTION
      3. HANDLING THE PARTICULARITIES OF RELIEF DISTRIBUTION NETWORKS
      4. LITERATURE REVIEW
      5. METHODOLOGICAL FRAMEWORK
      6. CONCLUSION
  9. Section 3: Supply Chain Operations
    1. Chapter 9: An Analytical Model to Estimate the Optimum Production Rate of Picking Processes in a Modular Warehouse Environment
      1. Abstract
      2. INTRODUCTION
      3. BRIEF LITERATURE REVIEW
      4. ANALYSIS OF THE PARAMETRIC MODEL
      5. ELEMENTS OF SPECIAL MODELS
      6. BASIC, NORMAL AND STANDARD TIMES
      7. PERFORMANCE MEASUREMENTS
      8. RESULTS AND DISCUSSION
      9. CONCLUSION
    2. Chapter 10: Constrained Optimization of JIT Manufacturing Systems with Hybrid Genetic Algorithm
      1. Abstract
      2. INTRODUCTION
      3. SYSTEM DESCRIPTION: JIT PRODUCTION CONTROL POLICIES
      4. OPTIMIZATION PROBLEM: OBJECTIVE FUNCTION
      5. EXPERIMENTAL RESULTS: SIMULATION CASE
      6. CONCLUSION AND FUTURE RESEARCH
    3. Chapter 11: Multi-period routing in Hybrid Courier Operations
      1. Abstract
      2. INTRODUCTION
      3. Main Concept
      4. Model for Allocating Flexible Service Calls to Expected Routes
      5. Proposed Methods
      6. Test Results: Allocation of Flexible Calls
      7. Case Study
      8. Conclusion
    4. Chapter 12: Dynamic Travel Time Estimation Techniques for Urban Freight Transportation Networks Using Historical and Real-Time Data
      1. Abstract
      2. INTRODUCTION
      3. BACKGROUND
      4. TRAVEL TIME PREDICTION METHODS
      5. EVALUATION OF TRAVEL TIME PREDICTION METHODS
      6. DESIGN OF EXPERIMENTS
      7. EXPERIMENTAL RESULTS
      8. CONCLUSION
  10. Compilation of References
  11. About the Contributors
  12. Index