Hybrid Evolutionary Strategy and Simulated Annealing Algorithms for Integrated Process Planning, Scheduling and Due-Date Assignment Problem

Abstract

Although integrated process planning and scheduling (IPPS) problem is studied extensively as scheduling with due-date assignment problem (SWDDA) in the literature, there are only a few studies on integration of these three manufacturing functions which are process planning, scheduling, and due-date assignment. Since outputs of upper stream functions effect downstream functions and higher integration gives a better global performance, it is better to integrate these three functions. In this study integration of process planning and earliest due-date scheduling (EDD) with due-date assignment is studied using hybrid evolutionary strategies (RS/ES) and hybrid simulated annealing algorithms (RS/SA). Ordinary solutions (OS), random search (RS) solutions, evolutionary strategies (ES) solutions, and simulated annealing (SA) solutions are compared with each other and hybrid solutions of ES and SA, with RS. According to the results, higher integration found better and best results are obtained with the highest integration level. ES and SA methods gave better results compared to the RS and OS, and RS/ES and RS/SA techniques were found promising search techniques.