Deakin University
Browse

File(s) under permanent embargo

An intelligent physarum solver for supply chain network design under profit maximization and oligopolistic competition

journal contribution
posted on 2017-01-01, 00:00 authored by X Zhang, F T S Chan, A Adamatzky, S Mahadevan, H Yang, Zili ZhangZili Zhang, Y Deng
We propose an efficient bio-inspired algorithm for design of optimal supply chain networks in a competitive oligopoly markets. The firms compete in manufacture, storage and distribution of a product to several markets. Each firm aims at maximisation of its own profit by optimising the design capacity and product flow in the supply chain. We model the supply chain network as a multi-layer graph of manufacturing nodes, distribution nodes and storage centres. To optimise the network, we adopt the mechanisms of a foraging behaviour of slime mould Physarum polycephalym. First, we extend the original Physarum model to deal with networks with multiple sources and sinks. Second, we develop a novel method to solve the user equilibrium (UE) problem by exploiting the adaptivity of the Physarum model: we update the link costs according to the product flow. Third, we refer to an equivalent transformation between system optimum problem and UE problem to determine the optimal product flows and design capacities of a supply chain. At last, we present an approach to update the amount of product supplied by each firm. By comparing our solutions with that in Nagurney (2010b) on several numerical examples, we demonstrate the efficiency and practicality of the proposed method.

History

Journal

International journal of production research

Volume

55

Issue

1

Pagination

244 - 263

Publisher

Taylor & Francis

Location

Abingdon, Eng.

ISSN

0020-7543

eISSN

1366-588X

Language

eng

Publication classification

C Journal article; C1.1 Refereed article in a scholarly journal

Copyright notice

2016, Informa UK Limited

Usage metrics

    Research Publications

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC