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The integrated application of effective approaches in supply chain networks /

Expanding the application of diverse techniques belonging to different branches of science, The Integrated Application of Effective Approaches in Supply Chain Networks creates coordination and integration for the analysis of supply network data.

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Detalles Bibliográficos
Autores principales: Rostamkhani, Ramin (Autor), Ramayah, Thurasamy (Autor)
Formato: Electrónico eBook
Lenguaje:inglés
Publicado: Leeds : Emerald Publishing Limited, 2024.
Colección:Emerald points.
Materias:
Business logistics.
Business & Economics / Logistics & Supply Chain.
Purchasing and supply management.
Distribution and logistics management.
Acceso en línea:https://doi.org/10.1108/9781835496305
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Tabla de Contenidos:
  • Intro
  • Halftitle Page
  • Title Page
  • Copyright Page
  • Contents
  • Preface
  • Introduction: A Brief History of the Combination of Different Branches of Science in
  • The Brief History of the Application of Mathematics in Supply Chain Networks
  • Probability and Statistics
  • Linear Algebra
  • Arithmetic
  • Mathematical Modeling
  • Logic and Algorithms
  • Conclusion
  • The Brief History of the Application of Operations Research in Supply Chain Networks
  • The Brief History of the Application of Management Concepts in Supply Chain Networks
  • References
  • Chapter 1: Mathematical Functions Approach: The Behavior Estimation of Data in Supply Chain Management
  • 1.1. Introduction
  • 1.2. Previous Studies in SCM Data
  • 1.3. Previous Studies in Statistical Distribution Functions
  • 1.4. A Summary of the Previous Studies
  • 1.5. Chapter Theoretical Framework
  • 1.5.1. Chapter Questions
  • 1.5.2. Chapter Objective
  • 1.5.3. Chapter Methodology
  • 1.6. The SCM Components
  • 1.7. The Popular Statistical Distribution Functions
  • 1.8. Numerical Applications
  • 1.8.1. Numerical Application in a Manufacturing Industry.
  • 1.8.2. Numerical Application in a Services Industry
  • 1.9. The Maximum Likelihood Estimator for the Reliability Functions
  • 1.10. The Assessment of Results
  • 1.10.1. The Assessment of Results in the Manufacturing Industry
  • 1.10.2. The Assessment of Results in the Services Industry
  • 1.11. Discussion of the Findings
  • 1.12. Conclusion
  • Appendix 1: AD Test Results on Manufacturing and Services Under Study Extracted by Minitab Software
  • Appendix 2: Maximum Likelihood Estimator on Manufacturing and Services Under Study Extracted by Excel Software.
  • Appendix 3: The Best Statistical Distribution Functions on Manufacturing and Services Under Study Extracted by Excel Software
  • References
  • Chapter 2: Operations Research Approach: Finding Suitable Techniques in Supply Chain Management
  • 2.1. Introduction
  • 2.2. Previous Studies in MLP on Supply Chain Data
  • 2.3. Previous Studies in QET on Supply Chain Data
  • 2.4. A Summary of the Previous Studies
  • 2.5. Chapter Theoretical Framework
  • 2.5.1. Chapter Questions
  • 2.5.2. Chapter Objective
  • 2.5.3. Chapter Methodology
  • 2.6. Process Analysis Method.
  • 2.7. Multiobjective Linear Programming
  • 2.8. An Empirical Case Study
  • 2.8.1. Case Illustrations
  • 2.9. Discussion and Results
  • 2.10. Conclusion
  • 2.10.1. Theoretical Contributions
  • 2.10.2. Recommendation for Policymakers
  • Appendix 4: The Definition of the Soft and Hard Classes in MLP
  • Appendix 5: The Used Questionnaire Related to Find the Suitable Soft and Hard Classes in This Study
  • Appendix 6: The Best Coefficients of Linear Equations in the SCM Components
  • Appendix 7: The Maximum Likelihood Values for the Coefficients of Parameters in the Linear Equations
  • Appendix 8: Questionnaire for the Final Assessment of the Proposed Operations Research Model.

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