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A Portfolio Optimization Approach to Selection in Multiobjective Evolutionary Algorithms

Lookup NU author(s): Dr Iryna Yevseyeva

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Abstract

© Springer International Publishing Switzerland 2014.In this work, a new approach to selection in multiobjective evolutionary algorithms (MOEAs) is proposed. It is based on the portfolio selection problem, which is well known in financial management. The idea of optimizing a portfolio of investments according to both expected return and risk is transferred to evolutionary selection, and fitness assignment is reinterpreted as the allocation of capital to the individuals in the population, while taking into account both individual quality and population diversity. The resulting selection procedure, which unifies parental and environmental selection, is instantiated by defining a suitable notion of (random) return for multiobjective optimization. Preliminary experiments on multiobjective multidimensional knapsack problem instances show that such a procedure is able to preserve diversity while promoting convergence towards the Pareto-optimal front.


Publication metadata

Author(s): Yevseyeva I, Guerreiro AP, Emmerich MTM, Fonseca CM

Publication type: Conference Proceedings (inc. Abstract)

Publication status: Published

Conference Name: PPSN 2014: Parallel Problem Solving from Nature – PPSN XIII

Year of Conference: 2014

Pages: 672-681

Online publication date: 17/09/2014

Acceptance date: 01/01/1900

Publisher: Springer, Cham

URL: https://doi.org/10.1007/978-3-319-10762-2_66

DOI: 10.1007/978-3-319-10762-2_66

Library holdings: Search Newcastle University Library for this item

Series Title: Lecture Notes in Computer Science

ISBN: 9783319107615


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