A multi-objective fuzzy flexible job shop scheduling problem considering the maximization of processing quality

Li, J.; Guan, Z.

Growing Science » International Journal of Industrial Engineering Computations » A multi-objective fuzzy flexible job shop scheduling problem considering the maximization of processing quality

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International Journal of Industrial Engineering Computations

ISSN 1923-2934 (Online) - ISSN 1923-2926 (Print) Quarterly Publication Volume 15 Issue 2 pp. 491-502 , 2024

A multi-objective fuzzy flexible job shop scheduling problem considering the maximization of processing quality Pages 491-502 Download PDF

Authors: Jiarui Li, Zailin Guan

DOI: 10.5267/j.ijiec.2023.12.011

Keywords: Fuzzy flexible job shop scheduling problem, Multi-objective optimization, Spider monkey optimization algorithm, Aircraft shaft parts manufacturing systems

Abstract: This paper analyzes practical production characteristics, including customer's stringent quality requirements and uncertain processing time in aircraft shaft parts manufacturing. Considering the above characteristics, we propose a multi-objective fuzzy aircraft shaft parts production scheduling problem considering the maximization of production quality. We define this problem as a multi-objective fuzzy flexible job shop scheduling problem (MO-fFJSP) with fuzzy processing time. To address this problem, we developed an improved multi-objective spider monkey optimization (IMOSMO) algorithm. IMOSMO integrates strategies such as genetic operators, variable neighborhood search and Pareto optimization theory on the framework of the conventional Spider Monkey Optimization (SMO) framework and discretize the continuous SMO algorithm to solve MO-fFJSP. To enhance the efficiency of the algorithm, we further adjust the sequence of the local leader learning phase and the global leader learning phase within the proposed IMOSMO framework. We conduct a comparative analysis between the performance of IMOSMO and NSGA-Ⅱ using 28 cases of varying scales. The computational results demonstrate the superiority of our algorithm over NSGA-Ⅱ in terms of both solution diversity and quality. Moreover, the performance of the proposed algorithm upgrades as the problem scale increases.

How to cite this paper

 Li, J & Guan, Z. (2024). A multi-objective fuzzy flexible job shop scheduling problem considering the maximization of processing quality.International Journal of Industrial Engineering Computations , 15(2), 491-502.

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