Solving flexible job shop scheduling using an effective memetic algorithm
by Wenchao Yi; Xinyu Li; Baolin Pan
International Journal of Computer Applications in Technology (IJCAT), Vol. 53, No. 2, 2016

Abstract: This paper proposes an effective Memetic Algorithm (MA) for the Flexible Job Shop Scheduling Problem (FJSP) with the objective of minimising the makespan. The proposed MA is a combination of TABU Search (TS) and Genetic Algorithm (GA). This hybridisation presents an effective way of performing both exploration and exploitation by incorporating the local search abilities of TS with the global reaching capabilities of GA. The approach provides an effective encoding method, genetic operators and neighbourhood structure in order to effectively solve the FJSP. To evaluate the performance of the proposed MA, several benchmark instances of FJSP have been used. The experimental results show that the proposed MA is a very effective method for solving FJSP.

Online publication date: Sun, 31-Jan-2016

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