An Evolution Strategy with Probabilistic Mutation for Multi-Objective Optimisation
Document Type
Conference Proceeding
Publisher
IEEE
Faculty
Faculty of Computing, Health and Science
School
School of Nursing and Public Health
RAS ID
1466
Abstract
Evolutionary algorithms have been applied with great success to the difficult field of multi-objective optimisation. Nevertheless, the need for improvements in this field is still strong. We present a new evolutionary algorithm, ESP (the Evolution Strategy with Probabilistic mutation). ESP extends traditional evolution strategies in two principal ways: it applies mutation probabilistically in a GA-like fashion, and it uses a new hypervolume based, parameterless, scaling independent measure for resolving ties during the selection process. ESP outperforms the state-of-the-art algorithms on a suite of benchmark multi-objective test functions using a range of popular metrics.
DOI
10.1109/CEC.2003.1299373
Comments
Huband, S., Hingston, P., While, L., & Barone, L. (2003, December). An evolution strategy with probabilistic mutation for multi-objective optimisation. In Evolutionary Computation, 2003. CEC'03. The 2003 Congress on (Vol. 4, pp. 2284-2291). IEEE. Available here.