Priority Decision Rules with a Fuzzy MCDM Approach for Solving Flexible Job Shop Problem: A Real Case Study of Optimizing Manufacturing

Abstract

The Flexible Job Shop Problem (FJSP) represents a significant challenge in the field of planning due to its complexity and the constant need for problem-solving in the market. It should be emphasized that FJSP is one of the most difficult NP problems in combinatorial optimization. One of the key factors in maintaining the competitiveness of small and medium enterprises in the market is increasing productivity while minimizing costs and manufacturing time. This paper proposes a multi-criteria approach, whose main role is job prioritization and FJSP optimization using a metaheuristic algorithm in a specific case study of a furniture manufacturing company. To determine the weight coefficients, two methods, the fuzzy Analytic Hierarchy Process (FAHP) and the fuzzy Full Consistency Method (FFUCOM), were integrated, while the fuzzy Weighted Aggregated Sum Product Assessment (FWASPAS) method was used for job ranking. As the next step in the study, the NSGA II algorithm was applied to optimize FJSP. Based on the conducted case study and production optimization, experimental results demonstrated the success of the proposed methodology and improved the organization of production resources after job prioritization.