Published

2012-03-01

EVOLUTIONARY MULTI-OBJECTIVE SCHEDULING PROCEDURES IN NON-STANDARDIZED PRODUCTION PROCESSES

Keywords:

Job-Shop scheduling, multi-objective optimization, Pareto frontier, memetic algorithm, local search (es)

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Authors

  • Mariano Frutos Universidad Nacional del Sur
  • Fernando Tohmé Universidad Nacional del Sur
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 of solutions (Pareto-optima) is better served by the use of genetic algorithms (GAs). In this work we analyze the performance of NSGAII (Non-dominated Sorting Genetic Algorithm II), SPEAII (Strength Pareto Evolutionary algorithm II) and their predecessors, NSGA and SPEA, when devoted to scheduling tasks in non-standardized production activities.

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How to Cite

[1]
M. Frutos and F. Tohmé, “EVOLUTIONARY MULTI-OBJECTIVE SCHEDULING PROCEDURES IN NON-STANDARDIZED PRODUCTION PROCESSES”, DYNA, vol. 79, no. 172, pp. 101–107, Mar. 2012, Accessed: Oct. 07, 2026. [Online]. Available: https://revistas.unal.edu.co/index.php/dyna/article/view/17552

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Copyright (c) 2012 DYNA

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