A decomposition based estimation of distribution algorithm for multiobjective knapsack problems

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

7 Scopus citations

Abstract

Multiobjective knapsack problems (MOKPs) are useful for both theoretical studies and practical applications. This paper proposes a novel algorithm, named multiobjective estimation of distribution algorithm based on decomposition (MEDA/D), for dealing with MOKPs. In MEDA/D, a probabilistic model based offspring reproduction operator is incorporated into the multiobjective evolutionary algorithm based on decomposition (MOEA/D). The population is maintained by the MOEA/D framework and new solutions are sampled from the probabilistic models. MEDA/D is applied to a set of test instances and compared with an MOEA/D with generic crossover/mutation operators. The statistical results show that the new approach is promising for dealing with MOKPs.

Original languageEnglish
Title of host publicationProceedings - 2012 8th International Conference on Natural Computation, ICNC 2012
Pages803-807
Number of pages5
DOIs
StatePublished - 2012
Event2012 8th International Conference on Natural Computation, ICNC 2012 - Chongqing, China
Duration: 29 May 201231 May 2012

Publication series

NameProceedings - International Conference on Natural Computation
ISSN (Print)2157-9555

Conference

Conference2012 8th International Conference on Natural Computation, ICNC 2012
Country/TerritoryChina
CityChongqing
Period29/05/1231/05/12

Fingerprint

Dive into the research topics of 'A decomposition based estimation of distribution algorithm for multiobjective knapsack problems'. Together they form a unique fingerprint.

Cite this