Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/75169
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Type: Journal article
Title: Evolutionary approaches for supply chain optimisation: Part I: single and two-component supply chains
Author: Ibrahimov, M.
Mohais, A.
Schellenberg, S.
Michalewicz, Z.
Citation: International Journal of Intelligent Computing and Cybernetics, 2012; 5(4):444-472
Publisher: Emerald Group Publishing Ltd
Issue Date: 2012
ISSN: 1756-378X
1756-3798
Statement of
Responsibility: 
Maksud Ibrahimov, Arvind Mohais and Sven Schellenberg, Zbigniew Michalewicz
Abstract: PURPOSE – The purpose of this paper and its companion (Part II: multi-silo supply chains) is to investigate methods to tackle complexities, constraints (including time-varying constraints) and other challenges. In tis part, the paper aims to devote attention to single silo and two-silo supply chains. It also aims to discuss three models. The first model is based on the winebottling real-world system and exposes complexities of a single operational component of the supply chain. The second model extends it to two components: production and distribution. The last system is a real-world implementation of the two-component supply chain. DESIGN/METHODOLOGY/APPROACH – Evolutionary approach is proposed for a single component problem. The two-component experimental supply chain is addressed by the algorithm based on cooperative coevolution. The final problem of steel sheet production is tackled with the evolutionary algorithm. FINDINGS – The proposed systems produce solutions better than solutions proposed by human experts and in a much shorter time. ORIGINALITY/VALUE – The paper discusses various algorithms to provide the decision support for the real-world problems. The proposed systems are in the production use.
Keywords: Genetic algorithms; Cooperative coevolution; Coordinated supply chain; Time-varying constraints; Supply chain management; Time-varying control systems
Rights: © Emerald Group Publishing Limited
RMID: 0020123349
DOI: 10.1108/17563781211282231
Appears in Collections:Computer Science publications

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