Solving the integrated production planning and scheduling problem via a new hybrid meta-heuristic algorithm

The subject of integrating production planning and control scheduling problems is becoming increasingly important, getting more and more attention in the complicated and constantly changing environment, presenting a new integrated model for aggregate production planning and scheduling problems, in which the production cost, total production time, changeover cost, and product delivery delays are minimized. After that, a new hybrid metaheuristic algorithm is proposed that combines the Whale Optimization Algorithm and the Grey Wolves Optimization Algorithm. The results are compared with different sample sizes using the standard algorithms (Genetic, Whale, and Greywolf) and dynamic programming based on mean square error. The results show that the hybrid meta-heuristic algorithm provides the best results.