Evolutionary approaches for supply chain optimisation Part I: single and two‐component supply chains

Evolutionary approaches for supply chain optimisation Part I: single and two‐component supply... 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. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Intelligent Computing and Cybernetics Emerald Publishing

Evolutionary approaches for supply chain optimisation Part I: single and two‐component supply chains

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Publisher
Emerald Publishing
Copyright
Copyright © 2012 Emerald Group Publishing Limited. All rights reserved.
ISSN
1756-378X
DOI
10.1108/17563781211282231
Publisher site
See Article on Publisher Site

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.

Journal

International Journal of Intelligent Computing and CyberneticsEmerald Publishing

Published: Nov 23, 2012

Keywords: Genetic algorithms; Cooperative coevolution; Coordinated supply chain; Time‐varying constraints; Supply chain management; Time‐varying control systems

References

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