A portfolio optimization approach to selection in multiobjective evolutionary algorithms
| dc.cclicence | CC-BY-NC-ND | en |
| dc.contributor.author | Yevseyeva, Iryna | en |
| dc.contributor.author | Guerreiro, A. P. | en |
| dc.contributor.author | Emmerich, M. T. M. | en |
| dc.contributor.author | Fonseca, C. M. | en |
| dc.date.acceptance | 2014-01-08 | en |
| dc.date.accessioned | 2017-03-28T13:08:25Z | |
| dc.date.available | 2017-03-28T13:08:25Z | |
| dc.date.issued | 2014-08 | |
| dc.description.abstract | 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. | en |
| dc.funder | Academy of Finland, European Commission Erasmus Mundus ECW Lot 6 | en |
| dc.identifier.citation | Yevseyeva I., Guerreiro A.P., Emmerich M.T.M., Fonseca C.M. (2014) A portfolio optimization approach to selection in multiobjective evolutionary algorithms. In: T. Bartz-Beielstein, J. Branke, B. Filipič, J. Smith (Eds.) Parallel Problem Solving from Nature – PPSN XIII. Ser. LNCS (vol. 8672), Springer, 2014, pp. 672-681 | en |
| dc.identifier.doi | https://doi.org/10.1007/978-3-319-10762-2_66 | |
| dc.identifier.uri | http://hdl.handle.net/2086/13919 | |
| dc.language.iso | en | en |
| dc.peerreviewed | Yes | en |
| dc.projectid | Academy of Finland grant number 126476. | en |
| dc.publisher | Springer | en |
| dc.researchgroup | Cyber Security Centre | en |
| dc.researchinstitute | Cyber Technology Institute (CTI) | en |
| dc.subject | Fitness assignment | en |
| dc.subject | portfolio selection | en |
| dc.subject | Sharpe ratio | en |
| dc.subject | evolutionary algorithms | en |
| dc.subject | multiobjective knapsack problem | en |
| dc.title | A portfolio optimization approach to selection in multiobjective evolutionary algorithms | en |
| dc.type | Article | en |