Solving multi-objective fuzzy flexible job shop scheduling problem using MABC algorithm

Article type: Research Article

Authors: Yuguang, Zhong^{; *} | Fan, Yang | Feng, Liu

Affiliations: College of Mechanical and Electrical Engineering, Harbin Engineering University, Harbin, China (PRC)

Correspondence: [*] Corresponding author. Zhong Yuguang, College of Mechanical and Electrical Engineering, Harbin Engineering University, Harbin 150001, China (PRC). Tel.: +86 0451 82519797; Fax: +86 0451 82569288; E-mail: [email protected].

Abstract: A new artificial bee colony algorithm called modified artificial bee colony algorithm (MABC) is presented to solve the multi-objective fuzzy flexible job-shop scheduling problem (MFFJSP) in this paper. The objectives of MFFJSP are to minimize the maximum fuzzy completion time (fuzzy makespan), maximize the weighted agreement index and minimize the maximum fuzzy machine workload. The three-point satisfaction-degree model is adopted to calculate the agreement index and this model can indicate the degree of satisfaction between the due date and the processing time. An effective local search operator based on variable neighborhood search (VNS) and crossover operator are embedded in this algorithm for obtaining good searching performance. In order to make the novel algorithm valid, we texted it, five benchmark instances and a practical case for the sake of effectiveness. Then, the performance of the proposed MABC has been compared with other existing algorithms to prove the superiority of this algorithm. In the end, the Taguchi method is used to investigate the impact of three key parameters from the MABC.

Keywords: Artificial bee colony algorithm, agreement index, variable neighborhood search, multi-objective fuzzy flexible job-shop scheduling problem

DOI: 10.3233/JIFS-181152

Journal: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 2, pp. 1455-1473, 2019