MOPED: a multi-objective Parzen-based estimation of distribution algorithm for continuous problems

Mario Costa, Edmondo Minisci

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

44 Citations (Scopus)

Abstract

An evolutionary multi-objective optimization tool based on an estimation of distribution algorithm is proposed. The algorithm uses the ranking method of non-dominated sorting genetic algorithm-II and the Parzen estimator to approximate the probability density of solutions lying on the Pareto front. The proposed algorithm has been applied to different types of test case problems and results show good performance of the overall optimization procedure in terms of the number of function evaluations. An alternative spreading technique that uses the Parzen estimator in the objective function space is proposed as well. When this technique is used, achieved results appear to be qualitatively equivalent to those previously obtained by adopting the crowding distance described in non-dominated sorting genetic algorithm-II.

LanguageEnglish
Title of host publicationEvolutionary Multi-Criterion Optimization
Subtitle of host publicationSecond International Conference, EMO 2003, Faro, Portugal, April 8–11, 2003. Proceedings
EditorsCarlos M. Fonseca, Peter J. Fleming, Eckart Zitzler, Lothar Thiele, Kalyanmoy Deb
Place of PublicationBerlin
PublisherSpringer
Pages282-294
Number of pages13
ISBN (Print)9783540018698, 9783540369707
DOIs
Publication statusPublished - 11 Apr 2003

Publication series

NameLecture Notes in Computer Science
PublisherSpringer Verlag
Volume2632
ISSN (Print)0302-9743

Fingerprint

Sorting algorithm
Sorting
Genetic algorithms
Genetic Algorithm
Estimator
Evolutionary multiobjective Optimization
Function evaluation
Pareto Front
Evaluation Function
Multiobjective optimization
Probability Density
Function Space
Ranking
Objective function
Optimization
Alternatives

Keywords

  • probability density function
  • Pareto front
  • distribution algorithm
  • objective function evaluation
  • multiobjective genetic algorithm

Cite this

Costa, M., & Minisci, E. (2003). MOPED: a multi-objective Parzen-based estimation of distribution algorithm for continuous problems. In C. M. Fonseca, P. J. Fleming, E. Zitzler, L. Thiele, & K. Deb (Eds.), Evolutionary Multi-Criterion Optimization: Second International Conference, EMO 2003, Faro, Portugal, April 8–11, 2003. Proceedings (pp. 282-294). (Lecture Notes in Computer Science; Vol. 2632). Berlin: Springer. https://doi.org/10.1007/3-540-36970-8_20
Costa, Mario ; Minisci, Edmondo. / MOPED : a multi-objective Parzen-based estimation of distribution algorithm for continuous problems. Evolutionary Multi-Criterion Optimization: Second International Conference, EMO 2003, Faro, Portugal, April 8–11, 2003. Proceedings. editor / Carlos M. Fonseca ; Peter J. Fleming ; Eckart Zitzler ; Lothar Thiele ; Kalyanmoy Deb. Berlin : Springer, 2003. pp. 282-294 (Lecture Notes in Computer Science).
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Costa, M & Minisci, E 2003, MOPED: a multi-objective Parzen-based estimation of distribution algorithm for continuous problems. in CM Fonseca, PJ Fleming, E Zitzler, L Thiele & K Deb (eds), Evolutionary Multi-Criterion Optimization: Second International Conference, EMO 2003, Faro, Portugal, April 8–11, 2003. Proceedings. Lecture Notes in Computer Science, vol. 2632, Springer, Berlin, pp. 282-294. https://doi.org/10.1007/3-540-36970-8_20

MOPED : a multi-objective Parzen-based estimation of distribution algorithm for continuous problems. / Costa, Mario; Minisci, Edmondo.

Evolutionary Multi-Criterion Optimization: Second International Conference, EMO 2003, Faro, Portugal, April 8–11, 2003. Proceedings. ed. / Carlos M. Fonseca; Peter J. Fleming; Eckart Zitzler; Lothar Thiele; Kalyanmoy Deb. Berlin : Springer, 2003. p. 282-294 (Lecture Notes in Computer Science; Vol. 2632).

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

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Costa M, Minisci E. MOPED: a multi-objective Parzen-based estimation of distribution algorithm for continuous problems. In Fonseca CM, Fleming PJ, Zitzler E, Thiele L, Deb K, editors, Evolutionary Multi-Criterion Optimization: Second International Conference, EMO 2003, Faro, Portugal, April 8–11, 2003. Proceedings. Berlin: Springer. 2003. p. 282-294. (Lecture Notes in Computer Science). https://doi.org/10.1007/3-540-36970-8_20