Engin, OrhanGüçlü, Abdullah2021-12-132021-12-1320181568-49461872-9681https://doi.org/10.1016/j.asoc.2018.08.002https://hdl.handle.net/20.500.13091/544This paper proposes an effective new hybrid ant colony algorithm based on crossover and mutation mechanism for no-wait flow shop scheduling with the criterion to minimize the maximum completion time. The no-wait flow shop is known as a typical NP-hard combinational optimization problem. The hybrid ant colony algorithm is applied to the 192 benchmark instances from literature in order to minimize makespan. The performance of the proposed Hybrid Ant Colony algorithm is compared to the Adaptive Learning Approach and Genetic Heuristic algorithm which are used in previous studies to solve the same set of benchmark problems. The computational experiments show that the proposed Hybrid Ant Colony algorithm provides better results relative to the other algorithms. (C) 2018 Elsevier B.V. All rights reserved.eninfo:eu-repo/semantics/closedAccessSchedulingNo-Wait Flow ShopHybrid Ant Colony AlgorithmMakespanParticle Swarm OptimizationIterated Greedy AlgorithmTotal Completion-TimeMakespan CriterionGenetic AlgorithmsMinimize MakespanSetup TimesIn-ProcessFlowshopsSearchArticle10.1016/j.asoc.2018.08.0022-s2.0-85052452159