Distributed permutation flowshop scheduling problem with total completion time objective

This paper considers the distributed permutation flowshop scheduling problem (DPFSP) which is an extension of permutation flowshop scheduling problem (PFSP). In DPFSP, there are multiple parallel factories instead of one factory as in PFSP. Each factory consists of same number of machines, and jobs can be processed in either of the factories to perform all necessary operations. This paper considers DPFSP for minimizing the total completion time objective. An MILP formulation is developed to find the optimal solution. To solve the problem, a metaheuristic, tabu search (TS) is proposed. Numerical experiments are performed on benchmark problem instances from the literature, and results of the proposed method are compared with current metaheuristics in the literature for this problem. The tabu search outperforms all existing metaheuristics in terms of solution quality.

Automated summary

This paper examines the distributed permutation flowshop scheduling problem (DPFSP) and proposes a metaheuristic approach, tabu search (TS), to solve the problem. Experimental results show that tabu search outperforms existing metaheuristics in terms of solution quality.