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A Physarum-inspired approach to supply chain network design

基于多头绒泡菌模型的供应链网络设计算法

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Abstract

A supply chain is a system which moves products from a supplier to customers, which plays a very important role in all economic activities. This paper proposes a novel algorithm for a supply chain network design inspired by biological principles of nutrients’ distribution in protoplasmic networks of slime mould Physarum polycephalum. The algorithm handles supply networks where capacity investments and product flows are decision variables, and the networks are required to satisfy product demands. Two features of the slime mould are adopted in our algorithm. The first is the continuity of flux during the iterative process, which is used in real-time updating of the costs associated with the supply links. The second feature is adaptivity. The supply chain can converge to an equilibrium state when costs are changed. Numerical examples are provided to illustrate the practicality and flexibility of the proposed method algorithm.

摘要

创新点

  1. 1.

    基于多头绒泡菌模型在迭代过程中的连续性, 提出了一种新的策略用来解决交通网络中的用户均衡问题;

  2. 2.

    利用用户均衡和系统最优之间的转化关系, 多头绒泡菌模型解决了最优供应链网络设计问题;

  3. 3.

    通过与现有算法相比较, 多头绒泡菌算法不仅找到了最优解, 而且迭代次数更少。

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Authors and Affiliations

  1. School of Computer and Information Science, Southwest University, Chongqing, 400715, China

    Xiaoge Zhang & Yong Deng

  2. Unconventional Computing Center, University of the West of England, Bristol, BS16 1QY, UK

    Andrew Adamatzky

  3. School of Science and Technology, Middlesex University, London, NW4 4BT, UK

    Xin-She Yang

  4. Department of Civil and Environmental Engineering, the Hong Kong University of Science and Technology, Hong Kong, China

    Hai Yang

  5. School of Engineering, Vanderbilt University, Nashville, 37235, USA

    Xiaoge Zhang, Sankaran Mahadevan & Yong Deng

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Correspondence to Yong Deng.

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Zhang, X., Adamatzky, A., Yang, XS. et al. A Physarum-inspired approach to supply chain network design. Sci. China Inf. Sci. 59, 052203 (2016). https://doi.org/10.1007/s11432-015-5417-4

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