@misc{10818/60143,
year = {2020},
url = {http://hdl.handle.net/10818/60143},
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. © 2020 The Society of Manufacturing Engineers},
publisher = {Journal of Manufacturing Systems},
title = {Multiobjective scheduling algorithm for flexible manufacturing systems with Petri nets},
doi = {10.1016/j.jmsy.2020.01.003},
author = {Mejía G. and Pereira J.},
}