A genetic local search algorithm for the multiple optimisation of the balanced academic curriculum problem

Carlos Castro, Broderick Crawford, Eric Monfroy

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

8 Scopus citations

Abstract

We deal with the Balanced Academic Curriculum Problem, a real world problem that is currently part of CSPLIB. We introduce a Genetic Local Search algorithm to solve this problem using two objectives which is a more realistic model than the one we used in our previous research. The tests carried out show that our algorithm obtains better solutions than systematic search techniques in the same amount of time.

Original languageEnglish
Title of host publicationCutting-Edge Research Topics on Multiple Criteria Decision Making
Subtitle of host publication20th International Conference, MCDM 2009, Chengdu/Jiuzhaigou, Proceedings
PublisherSpringer Verlag
Pages824-832
Number of pages9
ISBN (Print)9783642022975
DOIs
StatePublished - 2009

Publication series

NameCommunications in Computer and Information Science
Volume35
ISSN (Print)1865-0929

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