Abstract
In this paper, we study the application of a meta-heuristic to a two-machine flowshop scheduling problem. The meta-heuristic uses a branch-and-bound procedure to generate some information, which in turn is used to guide a genetic algorithm's search for optimal and near-optimal solutions. The criteria considered are makespan and average job flowtime. The problem has applications in flowshop environments where management is interested in reducing turn-around and job idle times simultaneously. We develop the combined branch-and-bound and genetic algorithm based procedure and two modified versions of it. Their performance is compared with that of three algorithms: pure branch-and-bound, pure genetic algorithm, and a heuristic. The results indicate that the combined approach and its modified versions are better than either of the pure strategies as well as the heuristic algorithm.
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Nagar, A., Heragu, S.S. & Haddock, J. A combined branch-and-bound and genetic algorithm based approach for a flowshop scheduling problem. Ann Oper Res 63, 397–414 (1996). https://doi.org/10.1007/BF02125405
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DOI: https://doi.org/10.1007/BF02125405