Evolutionary Multi-Objective Scheduling Procedures in Non-Standardized Production Processes

FRUTOS, MARIANO; FERNANDO TOHMÉ

DYNA

Universidad Nacional de Colombia, sede Medellín

Lugar: Medellín; Año: 2012 vol. 79 p. 101 - 107

0012-7353

Scheduling problems can be seen as multi-objective optimization problems (MOPs), involving the simultaneous satisfaction of several goals related to the optimal design, coordination, and management of tasks. The complexity of the goal functions and of the combinatorial methods used to find analytical solutions to them is quite high. The search for solutions (Pareto-optima) is better served by the use of genetic algorithms (GAs). In this paper, we analyze the performance of the non-dominated sorting genetic algorithm II (NSGAII), strength Pareto evolutionary algorithm II (SPEAII), and their predecessors, NSGA and SPEA, when these are devoted to scheduling tasks in non-standardized production activities.