Proposing a Pareto-based Multi-Objective Evolutionary Algorithm to Flexible Job Shop Scheduling Problem

During last decades, developing multi-objective evolutionary algorithms for optimization problems h as found considerable attention. Flexible job shop schedulin g problem, as an important scheduling optimization problem, has foun d this attention too. However, most of the multi-objective algorithm s that are developed for this problem use nonprofessional appr oaches. In another words, most of them combine their objective s and then solve multi-objective problem through single objective ap proaches. Of course, except some scarce researches that uses Par to-b sed algorithms. Therefore, in this paper, a new Paretobased algorithm called controlled elitism non-dominated sorting gen etic algorithm (CENSGA) is proposed for the multi-objective FJSP ( MOFJSP). Our considered objectives are makespan, critical machin e work load, and total work load of machines. The proposed algorith m is also compared with one the best Pareto-based algorithms of the literature on some multi-objective criteria, statistically. Keywords—Scheduling, Flexible job shop scheduling problem, controlled elitism non-dominated sorting genetic al gorithm