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A New Hybrid Genetic Algorithm to Deal with the Flow Shop Scheduling Problem for Makespan Minimization

Abstract : In the last years, many hybrid metaheuristics and heuristics combine one or more algorithmic ideas from different metaheuristics or even other techniques. This paper addresses the hybridization of a primitive ant colony algorithm inspired from the Pachycondyla apicalis behavior to search prey with the Genetic Algorithm to find near optimal solutions to solve the Flow Shop Scheduling Problem with makespan minimization. The developed algorithm is applied on different flow shop examples with diverse number of jobs. A sensitivity analysis was performed to define a good parameter choice for both the hybrid metaheuristic and the classical Genetic Algorithm. Computational results are given and show that the developed metaheuristic yields to a good quality solutions.
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Submitted on : Tuesday, November 6, 2018 - 5:23:23 PM
Last modification on : Thursday, November 8, 2018 - 1:38:06 PM
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Fatima Zohra Boumediene, Yamina Houbad, Ahmed Hassam, Latéfa Ghomri. A New Hybrid Genetic Algorithm to Deal with the Flow Shop Scheduling Problem for Makespan Minimization. 6th IFIP International Conference on Computational Intelligence and Its Applications (CIIA), May 2018, Oran, Algeria. pp.399-410, ⟨10.1007/978-3-319-89743-1_35⟩. ⟨hal-01913888⟩



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