Integrated production planning and scheduling with maintenance constraints in hybrid flow shop environment

Integrating production scheduling and scheduling is one of the most important decisions in any production organization that leads to increase the effectiveness of operations management. Long-term production planning decisions (determination of production quantity, inventory level, etc.) and short-term operational scheduling decisions (order of work processing and maintenance activities) have a direct effect on each other. In this study, a new mathematical model for simultaneous decision making of production planning and scheduling is presented with the aim of minimizing the total costs, time and delay in the hybrid flowshop. The concept of imperfect maintenance and considering several types of repair maintenance sources is presented in the proposed model. Two multi-objective meta-heuristic evolutionary algorithms based on the harmony search algorithm and the exact Epsilon-constraint solution method are proposed to solve the proposed model, which continuously searches the decision-making solution space. For this purpose, a sample of test problems of literature review and three performance criteria of Pareto number of solutions, mean ideal distance and Spacing metric are used to compare the results of meta-heuristic algorithms. The results show the advantages and effectiveness of the methods used in determining the Pareto optimal solution for optimization problems.