Title: A novel hybrid election campaign optimisation algorithm for multi-objective flexible job-shop scheduling problem

Authors: Shuting Wang; Chuanjiang Liu; Dawei Pei; Jinjiang Wang

Addresses: School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China ' School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China ' Qinghai No. 1 Machine Tool Co, Ltd., Qinghai Province, 810018, China ' Qinghai No. 1 Machine Tool Co, Ltd., Qinghai Province, 810018, China

Abstract: Flexible job-shop problem (FJSP) is an extension of the job shop problem that allows an operation to be processed by any machine from a given set along different routes. This paper presents a novel hybrid election campaign optimisation (ECO) algorithm combining with tabu search (TS) algorithm for solving the multi-objective FJSP to minimise the makespan, the total workload of all machines, and the workload of the busiest machine. ECO, as a new meta-heuristic, which integrates local search and global search scheme possesses high global search efficiency, TS, as a traditional meta-heuristic which possesses high local search ability. Through reasonably hybridising these two optimisation algorithms, an effective hybrid approach (ECO+TS), which makes full advantages of ECO and TS has been proposed for the multi-objective FJSP. The computational results have proved that the proposed hybrid algorithm is an efficient and effective approach to solve the multi-objective FJSP.

Keywords: flexible scheduling; job shop scheduling; multi-objective optimisation; election campaign optimisation; tabu search.

DOI: 10.1504/IJMSI.2013.055113

International Journal of Materials and Structural Integrity, 2013 Vol.7 No.1/2/3, pp.160 - 170

Available online: 16 Jul 2013 *

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