Dynamic fitness inheritance proportion for multi-objective particle swarm optimization

Authors:
Margarita Reyes-Sierra;Carlos A. Coello Coello
Affiliations:
CINVESTAV-IPN (Evolutionary Computation Group), Col. San Pedro Zacatenco, M&@233/xico D.F., Mé/xico;CINVESTAV-IPN (Evolutionary Computation Group), Col. San Pedro Zacatenco, M&@233/xico D.F., Mé/xico
Venue:
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Year:
2006

Citing 3
Cited 1

Fitness inheritance in genetic algorithms

SAC '95 Proceedings of the 1995 ACM symposium on Applied computing
Comparison of Multiobjective Evolutionary Algorithms: Empirical Results

Evolutionary Computation
Improving PSO-Based multi-objective optimization using crowding, mutation and ∈-dominance

EMO'05 Proceedings of the Third international conference on Evolutionary Multi-Criterion Optimization

Evolutionary hidden information detection by granulation-based fitness approximation

Applied Soft Computing

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Abstract

In this paper, we propose a dynamic mechanism to vary the probability by which fitness inheritance is applied throughout the run of a multi-objective particle swarm optimizer, in order to obtain a greater reduction in computational cost (than the obtained with a fixed probability), without dramatically affecting the quality of the results. The results obtained show that it is possible to reduce the computational cost by 32% without affecting the quality of the obtained Pareto front.