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Assist. Abd Elrahman Nabawy Ahmed Elgendy :: Publications:

Title:
Optimizing Dynamic Flexible Job Shop Scheduling Problem Based on Genetic Algorithm
Authors: Abd Elrahman Elgendy, Mohammed Hussein, Abdelmoty Elhakeem
Year: 2017
Keywords: Flexible Job Shop Scheduling Problem, Dynamic Job Shop Scheduling Problem, Genetic Algorithm, Rescheduling strategy
Journal: International Journal of Current Engineering and Technology,
Volume: Vol.7, No.2
Issue: Not Available
Pages: Not Available
Publisher: Inpressco
Local/International: International
Paper Link:
Full paper Abd Elrahman Nabawy Ahmed Elgendy_Optimizing Dynamic Flexible Job Shop Scheduling Problem Based on Genetic Algorithm.pdf
Supplementary materials Not Available
Abstract:

Scheduling the flexible job shop in the dynamic environment, in which arriving new job, the breakdown of machines and processing time variation are possible, is the most complex problem in the manufacturing system until now. A genetic algorithm (GA) was developed to deal with the problem related to flexible job shop scheduling problem represented in routing and sequencing the operations, besides the problem related to dynamic environment represented in appearing new events such as new job arrival and processing time variation. The algorithm incorporated the traditional procedures of GA with a repair strategy in order to optimize the makespan of dynamic flexible job shop scheduling problem (DFJSSP). The results indicate that the proposed algorithm is effective for solving DFJSSP.

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