Year: 2005
Type: article
Abstract: The NBI-NLPQLP optimization method is tested on several multi-objective optimization problems. Its performance is compared to that of MOGA-II: since NBI-NLPQLP is based on the classical gradient-based NLPQLP, it is fast and accurate, but not as robust, in comparison with the genetic algorithm. Furthermore a discontinuous Pareto frontier can give rise to problems in the NBI´s convergence. In order to overcome this problem, a hybridization technique coupled with a partitioning method is proposed.
Authors: Rigoni, Enrico, Poles, Silvia
Language: English
Subfield: Computational Theory and Mathematics
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W119087972