Jolai, F., zandieh, M., Naderi, B. (2010). A Memetic Algorithm for Hybrid Flowshops with Flexible Machine
Availability Constraints. Journal of Optimization in Industrial Engineering, Volume 2(Issue 3), 59-64.
Fariborz Jolai; mostafa zandieh; Bahman Naderi. "A Memetic Algorithm for Hybrid Flowshops with Flexible Machine
Availability Constraints". Journal of Optimization in Industrial Engineering, Volume 2, Issue 3, 2010, 59-64.
Jolai, F., zandieh, M., Naderi, B. (2010). 'A Memetic Algorithm for Hybrid Flowshops with Flexible Machine
Availability Constraints', Journal of Optimization in Industrial Engineering, Volume 2(Issue 3), pp. 59-64.
Jolai, F., zandieh, M., Naderi, B. A Memetic Algorithm for Hybrid Flowshops with Flexible Machine
Availability Constraints. Journal of Optimization in Industrial Engineering, 2010; Volume 2(Issue 3): 59-64.
A Memetic Algorithm for Hybrid Flowshops with Flexible Machine
Availability Constraints
1Department of industrial engineering, faculty of engineering, University of Tehran, Tehran, Iran
2Department of industrial management, management and accounting faculty, Shahid Beheshti University, Tehran, Iran
3Department of indusrial engineering, Amirkabir University of Technology, Tehran, Iran
Abstract
This paper considers the problem of scheduling hybrid flowshops with machine availability constraints (MAC) to minimize makespan. The paper deals with a specific case of MAC caused by preventive maintenance (PM) operations. Contrary to previous papers considering fixed or/and conservative policies, we explore a case in which PM activities might be postponed or expedited while necessary. Regarding this flexibility in PM activities, we expect to obtain more efficient schedule. A simple technique is employed to schedule production jobs along with the flexible MACs caused by PM. To solve the problem, we present a high performing metaheuristic based on memetic algorithm incorporating some advanced features. To evaluate the proposed algorithm, the paper compares the proposed algorithm with several wellknown algorithms taken from the literature. Finally, we conclude that the proposed algorithm outperforms other algorithms.
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