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Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/13102

Title: Comparison of three meta heuristics to optimize hybrid flow shop scheduling problem with parallel machines
Authors: Syam, W.P.a,
Al-Harkan, I.M.
Keywords: Flow shop; Genetic algorithm; Simulated annealing; Tabu search
Issue Date: 2010
Publisher: World Academy of Science
Citation: Proceedings of World Academy of Science, Engineering and Technology, 62,271-278.
Abstract: This study compares three meta heuristics to minimize makespan (Cmax) for Hybrid Flow Shop (HFS) Scheduling Problem with Parallel Machines. This problem is known to be NP-Hard. This study proposes three algorithms among improvement heuristic searches which are: Genetic Algorithm (GA), Simulated Annealing (SA), and Tabu Search (TS). SA and TS are known as deterministic improvement heuristic search. GA is known as stochastic improvement heuristic search. A comprehensive comparison from these three improvement heuristic searches is presented. The results for the experiments conducted show that TS is effective and efficient to solve HFS scheduling problems.
URI: http://hdl.handle.net/123456789/13102
ISSN: 20703740
Appears in Collections:College of Engineering

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