An efficient tabu search algorithm for the distributed permutation flowshop scheduling problem

Abstract

Distributed permutation flow shop scheduling problem (DPFSP) is a newly proposed scheduling problem, which is a generalisation of classical permutation flowshop scheduling problem. Studies on algorithms for solving this problem are in the early stage. In this paper, we propose a new tabu algorithm for solving this problem, which exploits a novel tabu strategy. A method that swaps sub-sequences of jobs is presented to generate neighbourhood. Moreover, an enhanced local search method is proposed and also combined into the tabu algorithm. We also use the well-known benchmark of Taillard (extended to the distributed permutation flowshop problems) to test the algorithm. From the intensive experiments we carried out, we conclude that the proposed tabu algorithm outperforms all the existing algorithms including heuristics algorithms (i.e. NEH1, NEH2, VND(a) and VND(b)) and a hybrid genetic algorithm, so the best-known solutions for 472 instances are updated. Moreover, it is worth mentioning that the efficiency of the tabu algorithm is also better than that of the genetic algorithm.

Keywords:

• tabu search
• distributed scheduling
• flowshop
• sequence swapping

Acknowledgements

We would like to thank the anonymous reviewers for their valuable comments which have helped us to improve this paper. This work is supported by the National Natural Science Foundation of China (No. 61175056), the Major Projects of Technology Bureau of Dalian (No. 2007A14GXD42), and the Dalian Maritime University Backbone Youth Foundation (No. 2011QN033, No. 2009JC29).