Fuzzy Programming for Parallel Machines Scheduling: Minimizing Weighted Tardiness/Earliness and Flow time through Genetic Algorithm

Appropriate scheduling and sequencing of tasks on machines is one of the basic and significant problems that a shop or a factory managerencounters; this is why in recent decades extensive researches have been done on scheduling issues. A type of scheduling problems is justin-time (JIT) scheduling and in this area, motivated by JIT manufacturing, this study investigates a mathematical model for appraising amulti-objective programing that minimize total weighted tardiness, earliness and total flow time with fuzzy parameters on parallelmachines, simultaneously with respect to the impact of machine deterioration. Besides, in this paper, attempts are made to present adefuzzification approach and a heuristic method based genetic algorithm (GA) to solve the proposed model. Finally, several dominanceproperties of optimal solutions are demonstrated in comparison with the results of a state-of-the-art commercial solver and the simulatedannealing method that is followed by illustrating some instances for indicating validity and efficiency of the method

Keywords:

Mathematical optimization , Fuzzy multi-objective model , Parallel machines scheduling , Weighted tardiness/earliness , Genetic algorithm