Publication: A multi-objective ant colony system algorithm for flow shop scheduling problem
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Authors
Yağmahan, Betül
Authors
Yenisey, Mehmet Mutlu
Advisor
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Pergamon-Elsevier Science
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Abstract
In this paper, we consider the flow shop scheduling problem with respect to the both objectives of makespan and total flowtime. This problem is known to be NP-hard type in literature Several algorithms have been proposed to solve this problem We present a multi-objective ant colony system algorithm (MOACSA). which combines ant colony optimization approach and a local search strategy in order to solve this scheduling problem. The proposed algorithm is tested with well-known problems in literature Its solution performance was compared with the existing multi-objective heuristics. The Computational results show that proposed algorithm is more efficient and better than other methods compared.
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Keywords
Flow shop scheduling, Multi-objective, Makespan, Flowtime, Heuristics, Ant colony optimization, Tabu search algorithm, Optimization algorithm, Genetic algorithms, M-machine, Minimize, Makespan, Time, Computer science, Engineering, Operations research & management science, Computational complexity, Computational efficiency, Heuristic methods, Machine shop practice, Multiobjective optimization, Scheduling algorithms, Ant-colony optimization, Flow-shop scheduling, Flow-time, Multi objective, Problem solving
Citation
Yağmahan, B. ve Yenisey, M. M. (2010). "A multi-objective ant colony system algorithm for flow shop scheduling problem". Expert Systems with Applications, 378(2), 1361-1368.