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

Shuzhu Zhang, Ka Man Lee, Kan Wu, King Lun Tommy Choy

Research output: Journal article publicationJournal articleAcademic researchpeer-review

86 Citations (Scopus)


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
Publication statusPublished - 15 Dec 2016


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

ASJC Scopus subject areas

  • Engineering(all)
  • Computer Science Applications
  • Artificial Intelligence


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