Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/62067
Title: Multi-objective optimization for sustainable supply chain network design considering multiple distribution channels
Authors: Zhang, S
Lee, CKM 
Wu, K
Choy, KL 
Keywords: Artificial bee colony
Multi-objective optimization
Multiple distribution channels
Supply chain network
Swarm intelligence
Issue Date: 2016
Publisher: Pergamon Press
Source: Expert systems with applications, 2016, v. 65, p. 87-99 How to cite?
Journal: Expert systems with applications 
Abstract: The emergence of Omni-channel has affected the practical design of the supply chain network (SCN) with the purpose of providing better products and services for customers. In contrast to the conventional SCN, a new strategic model for designing SCN with multiple distribution channels (MDCSCN) is introduced in this research. The MDCSCN model benefits customers by providing direct products and services from available facilities instead of the conventional flow of products and services. Sustainable objectives, i.e., reducing economic cost, enlarging customer coverage and weakening environmental influences, are involved in designing the MDCSN. A modified multi-objective artificial bee colony (MOABC) algorithm is introduced to solve the MDCSCN model, which integrates the priority-based encoding mechanism, the Pareto optimality and the swarm intelligence of the bee colony. The effect of the MDCSCN model are examined and validated through numerical experiment. The MDCSCN model is innovative and pioneering as it meets the latest requirements and outperforms the conventional SCN. More importantly, it builds the foundation for an intelligent customer order assignment system. The effectiveness and efficiency of the MOABC algorithm is evaluated in comparison with the other popular multi-objective meta-heuristic algorithm with promising results.
URI: http://hdl.handle.net/10397/62067
ISSN: 0957-4174
EISSN: 1873-6793
DOI: 10.1016/j.eswa.2016.08.037
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