Multiobjective scheduling algorithm for flexible manufacturing systems with Petri nets. (January 2020) - Mejía, Gonzalo; Pereira, Jordi
Highlights: Two Petri net-based algorithms for FMS scheduling are proposed: NSGAII and WGA. Both NSGA II and WGA found new best solutions on some scheduling problems. The NSGA II finds better Pareto Fronts in comparison with the WGA. The WGA finds better extreme solutions in comparison with the NSGA II. Both NSGA II and WGA find near-optimal Pareto fronts in classical job shop problems. Abstract: In this work, we focus on general multi-objective scheduling problems that can be modeled using a Petri net framework. Due to their generality, Petri nets are a useful abstraction that captures multiple characteristics of real-life processes. To provide a general solution procedure for the abstraction, we propose three alternative approaches using an indirect scheme to represent the solution: (1) a genetic algorithm that combines two objectives through a weighted fitness function, (2) a non dominated sorting genetic algorithm (NSGA-II) that explicitly addresses the multi-objective nature of the problem and (3) a multi-objective local search approach that simultaneously explores multiple candidate solutions. These algorithms are tested in an extensive computational experiment showing the applicability of this general framework to obtain quality solutions.