Multi-objective optimization for sustainable supply chain network design considering multiple distribution channels

Shuzhu Zhang, Carman Ka Man Lee*, Kan Wu, King Lun Choy

*Corresponding author for this work

Research output: Contribution to journalJournal Article peer-review

91 Scopus citations


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.

Original languageEnglish
Pages (from-to)87-99
Number of pages13
JournalExpert Systems with Applications
StatePublished - 15 12 2016
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2016 Elsevier Ltd


  • Artificial bee colony
  • Multi-objective optimization
  • Multiple distribution channels
  • Supply chain network
  • Swarm intelligence


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