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Optimization of Integrated Supply Chain Planning under Multiple Uncertainty

  • Book
  • © 2015

Overview

Authors:
  1. Juping Shao

    1. School of Business, Suzhou Uni. of Science and Technology, Suzhou, China

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  2. Yanan Sun

    1. Suzhou Industrial Park Anwood Logistics System co., Ltd., Suzhou, China

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  3. Bernd Noche

    1. Institute for Transport Systems and Logistics, University Duisburg-Essen, Duisburg, Germany

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  • Puts forward a dynamic equation model of customer demand and testifies the correctness and reliability of the model with numerical examples

  • Builds three kinds of integrated novel supply chain logistics planning models on different control types

  • Designs three kinds of novel hybrid intelligence algorithms Verifies the effectiveness of the models and algorithms with numerical experiments

  • Includes supplementary material: sn.pub/extras

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Table of contents (7 chapters)

  1. Front Matter

    Pages i-xvii
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  2. Introduction

    • Juping Shao, Yanan Sun, Bernd Noche
    Pages 1-7

  3. Literature Review

    • Juping Shao, Yanan Sun, Bernd Noche
    Pages 9-35

  4. Demand Forecasting Dynamic Equation Model

    • Juping Shao, Yanan Sun, Bernd Noche
    Pages 37-55

  5. Optimization of Strategic Alliance Supply Chain Logistics Planning Under Uncertain Environment

    • Juping Shao, Yanan Sun, Bernd Noche
    Pages 57-99

  6. Optimization of Decentralized Control Supply Chain Logistics Planning Under Uncertain Environment

    • Juping Shao, Yanan Sun, Bernd Noche
    Pages 101-147

  7. Optimization of Mixed Control Supply Chain Logistics Planning Under Uncertain Environment

    • Juping Shao, Yanan Sun, Bernd Noche
    Pages 149-183

  8. Conclusion and Future Work

    • Juping Shao, Yanan Sun, Bernd Noche
    Pages 185-188
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Keywords

About this book

​The subject of this book is supply chain logistics planning optimization under multiple uncertainties, the key issue in supply chain management.  Focusing on the strategic-alliance three-level supply chain, the model of supply chain logistics planning was established in terms of the market prices and the market requirements as random variables of manufactured goods with random expected value programming theory, and the hybrid intelligence algorithm solution model was designed. Aiming at the decentralized control supply chain, in which the nodes were unlimited expansion, the chance-constrained stochastic programming model was created in order to obtain optimal decision-making at a certain confidence level. In addition, the hybrid intelligence algorithm model was designed to solve the problem of supply chain logistics planning with the prices of the raw-materials supply market of the upstream enterprises and the prices of market demand for products of the downstream enterprises as random variables in the supply chain unit. Aimed at the three-stage mixed control supply chain, a logistics planning model was designed using fuzzy random programming theory with customer demand as fuzzy random variables and a hybrid intelligence algorithm solution was created. The research has significance both in theory and practice. Its theoretical significance is that the research can complement and perfect existing supply chain planning in terms of quantification. Its practical significance is that the results will guide companies in supply chain logistics planning in the uncertain environment.

Authors and Affiliations

  • School of Business, Suzhou Uni. of Science and Technology, Suzhou, China

    Juping Shao

  • Suzhou Industrial Park Anwood Logistics System co., Ltd., Suzhou, China

    Yanan Sun

  • Institute for Transport Systems and Logistics, University Duisburg-Essen, Duisburg, Germany

    Bernd Noche

Bibliographic Information

  • Book Title: Optimization of Integrated Supply Chain Planning under Multiple Uncertainty

  • Authors: Juping Shao, Yanan Sun, Bernd Noche

  • DOI: https://doi.org/10.1007/978-3-662-47250-7

  • Publisher: Springer Berlin, Heidelberg

  • eBook Packages: Business and Economics, Business and Management (R0)

  • Copyright Information: Springer-Verlag Berlin Heidelberg 2015

  • Hardcover ISBN: 978-3-662-47249-1Published: 10 June 2015

  • Softcover ISBN: 978-3-662-51617-1Published: 18 October 2016

  • eBook ISBN: 978-3-662-47250-7Published: 27 May 2015

  • Edition Number: 1

  • Number of Pages: XVII, 188

  • Number of Illustrations: 47 b/w illustrations

  • Topics: Supply Chain Management, Development Economics, Market Research/Competitive Intelligence

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