Ant Colony Algorithm And Multi-Agent-Based Production Scheduling Optimization Model

Journal Title: Malaysian E Commerce Journal (MECJ) - Year 2017, Vol 1, Issue 1

Abstract

In the dynamic production environment of supply chain, based on information sharing among enterprises of supply chain, this paper puts forward a production scheduling optimization model for supply chain. It transforms the choice of cooperative enterprises and their process ordering into the choice of path in graph theory. With respect to the complexity of model solving, this paper designs an expert system aided multi-agent intelligent ant colony algorithm to solve the production scheduling optimization model, where ant colony is constructed with multi-agent and the order decomposition structure and constraint are expressed by expert system. Also, supply chain production scheduling optimization prototype architecture is implemented and the related technologies are given in the paper. Finally using the system,several experiments are conducted,which show that both of the model and the algorithm are effective and feasible.

Authors and Affiliations

Jinghua zhao, Jie Lin, Xia Zhao

Keywords

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  • EP ID EP404486
  • DOI 10.26480/mecj.01.2017.01.06
  • Views 96
  • Downloads 0

How To Cite

Jinghua zhao, Jie Lin, Xia Zhao (2017). Ant Colony Algorithm And Multi-Agent-Based Production Scheduling Optimization Model. Malaysian E Commerce Journal (MECJ), 1(1), 1-6. https://europub.co.uk./articles/-A-404486