Solving Flow Shop Scheduling Problems Using a Hybrid Genetic Scatter Search Algorithm
نویسنده
چکیده
In this paper we consider n-jobs, m-machines permutation flow shop scheduling problems. Flow shop scheduling is one of the most important combinational optimization problems. The permutation flow shop scheduling problems are NP-Hard (Non deterministic Polynomial time Hard). Hence many heuristics and metaheuristics were addressed in the literature to solve these problems. In this paper a hybrid genetic scatter search algorithm (HGSSA) is presented to minimize the makespan for the permutation flow shop scheduling problems. An effective constructive heuristics is incorporated with the initial solutions to obtain the optimal or near-optimal solutions rapidly. The performance of the proposed algorithm has been tested with the benchmark problems addressed in the literature. The results are compared with some other meta-heuristics algorithms. The results show that the proposed algorithm is efficient in producing optimal or near-optimal solutions.
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