Distributed Tabu Searches in Multi-agent System for Permutation Flow Shop Scheduling Problem

In this paper, we propose a distributed multi-agent approach to solve the permutation flow shop scheduling problem for the objective of minimizing the makespan. This approach consists of two types of agents that cooperate to find a solution for this problem. A mediator agent who is responsible for generating the initial solution with NEHT heuristic, and scheduler agents, each applying a tabu search to refine a specific sequence of jobs which differs from those of other agents. Computational experiments confirm that our approach provides good results equal to or better than the ones given by other approaches with which we have made comparisons.