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A Hybrid Genetic Algorithm for Job Shop Scheduling Problem to Minimize Makespan

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2 Author(s)
Lin Liu ; Dept. of Autom., Shanghai Jiaotong Univ. ; Yugeng Xi

A hybrid genetic algorithm is presented for the job shop scheduling problem. The chromosome representation is based on random keys. A chromosome includes genes representing the relative priorities of all operations and genes determining the idle time permitted on a machine before processing an operation. The SPV (smallest position value) rule is used to convert a real number vector to a job repetition representation. Then the schedule is constructed using the hybrid scheduler that introduces parameters to control the scope of search space. Finally, a neighborhood-based local search is used to improve the solution quality. The experimental results on the well-known benchmark instances show the proposed algorithm is very effective and competitive with other methods in literatures

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Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on  (Volume:1 )

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