New mathematical modeling and a constructive heuristic algorithm for integrated process planning and scheduling

Recent advances in manufacturing systems and multifunction machines have caused products to be produced through several alternative process plans. Therefore, the integration of process planning and scheduling, as two of the most critical functions, becomes essential to enhance manufacturing systems’ productivity. Several different algorithms have solved the integrated process planning and scheduling (IPPS) problem in the literature. All proposed algorithms require a list of available process plans in advance (type-1). In this paper, an efficient mixed-integer linear programming (MILP) model is presented based on the term "combination." Besides, a type-2 priority-based heuristic algorithm (PBHA II) is proposed using dispatching rules with prioritizing jobs, combinations, and operations to solve the IPPS problems expressed by AND/OR graphs and with a makespan criterion. The MILP model and proposed heuristic algorithm are tested on the most challenging benchmark problems. Experimental results show the superiority of the MILP model over the best one in the literature, as well as the effectiveness and high performance of PBHA II. New upper bounds have been obtained in a short computational time for 7 of 24 most complex problems, which have been used by many researchers over the last two decades.