Solving Hard Multiobjective Problems with a Hybridized Method


  • Leticia Cagnina LIDIC (Research Group). Universidad Nacional de San Luis, Ej. de Los Andes 950 - (5700) San Luis, Argentina.
  • Susana Cecilia Esquivel LIDIC (Research Group). Universidad Nacional de San Luis, Ej. de Los Andes 950 - (5700) San Luis, Argentina.


Particle Swarm Optimization, Multi-objective Optimization, Epsilon-constraint Method


This paper presents a hybrid method to solve hard multiobjective problems. The proposed approach adopts an epsilon-constraint method which uses a Particle Swarm Optimizer to get points near of the true Pareto front. In this approach, only few points will be generated and then, new intermediate points will be calculated using an interpolation method, to increase the among of points in the output Pareto front. The proposed approach is validated using two difficult multiobjective test problems and the results are compared with those obtained by a multiobjective evolutionary algorithm representative of the state of the art: NSGA-II.


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How to Cite

Cagnina, L., & Esquivel, S. C. (2010). Solving Hard Multiobjective Problems with a Hybridized Method. Journal of Computer Science and Technology, 10(03), p. 117–122. Retrieved from



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