Hybrid optimization of production scheduling and maintenance using mathematical programming and NSGA-II meta-heuristic method

This paper presents an integrated hybrid optimization problem for production and maintenance scheduling within a comprehensive system using overall cost and reliability. The total cost consists of three parts: production costs, inventory costs, and workforce costs. This integration aims to simultaneously find the optimal value of the function in a period. Using mixed-integer linear programming, the optimal values ​​are minimized over a limited horizon in the various samples considered for different numbers of workers and machines. In order to evaluate the model in larger dimensions, the NSGA-II metaheuristic method has been used. Given that the error rate of the developed mathematical model with the results of the meta-heuristic method in small dimensions can be neglected, so this meta-heuristic method has been used to perform sensitivity analysis in larger dimensions of the problem. In general, the results of this paper provide valuable information about changes in the number of workers and machines simultaneously to prevent interruptions and save on production to managers and analysts in the field of production planning.