Effect of solution representations on Tabu search in scheduling applications

Authors:
Chen-Fu Chen;Muh-Cherng Wu;Keng-Han Lin
Affiliations:
-;-;-
Venue:
Computers and Operations Research
Year:
2013

Citing 13
Cited 0

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Abstract

This research investigates the application of meta-heuristic algorithms to a scheduling problem called permutation manufacturing-cell flow shop (PMFS) from two perspectives. First, we examine the effect of using different solution representations (S"n"e"w and S"o"l"d) while applying Tabu-search algorithm. Experimental results reveal that Tabu_S"n"e"w outperforms Tabu_S"o"l"d. The rationale why Tabu_S"n"e"w is superior is further examined by characterizing the intermediate outcomes of the evolutionary processes in these two algorithms. We find that the superiority of S"n"e"w is due to its relatively higher degree of freedom in modeling Tabu neighborhood. Second, we propose a new algorithm GA_Tabu_S"n"e"w, which empirically outperforms the state-of-the-art meta-heuristic algorithms in solving the PMFS problem. This research highlights the importance of solution representation in the application of meta-heuristic algorithm, and establishes a significant milestone in solving the PMFS problem.