2014

Conférence

Genetic and Evolutionary Computation Conference, (GECCO’14), Canada, 85-86

In this paper, we propose an Indicator-based Chemical Reaction Optimization (ICRO) algorithm for multiobjective optimization. There are two main motivations behind this work. On the one hand, CRO is a new recently proposed metaheuristic which demonstrated very good performance in solving several mono-objective problems. On the other hand, the idea of performing selection in Multi-Objective Evolutionary Algorithms (MOEAs) based on the optimization of a quality metric has shown a big promise in tackling Multi-Objective Problems (MOPs). The statistical analysis of the obtained results shows that ICRO provides competitive and better results than several other MOEAs.

@inproceedings{chaabani2015improved,
  title={An improved co-evolutionary decomposition-based algorithm for bi-level combinatorial optimization},
  author={Chaabani, Abir and Bechikh, Slim and Ben Said, Lamjed and Azzouz, Radhia},
  booktitle={Proceedings of the Companion Publication of the 2015 Annual Conference on Genetic and Evolutionary Computation},
  pages={1363--1364},
  year={2015}
}