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

Carlos Castro; Broderick Crawford; Eric Monfroy

doi:10.1007/978-3-642-02298-2_119

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 proceeding › Conference contribution › peer-review

7 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 language	English
Title of host publication	Cutting-Edge Research Topics on Multiple Criteria Decision Making
Subtitle of host publication	20th International Conference, MCDM 2009, Chengdu/Jiuzhaigou, Proceedings
Pages	824-832
Number of pages	9
DOIs	https://doi.org/10.1007/978-3-642-02298-2_119
State	Published - 2009
Externally published	Yes

Publication series

Name	Communications in Computer and Information Science
Volume	35
ISSN (Print)	1865-0929

Access to Document

10.1007/978-3-642-02298-2_119

Cite this

Castro, C., Crawford, B., & Monfroy, E. (2009). A genetic local search algorithm for the multiple optimisation of the balanced academic curriculum problem. In Cutting-Edge Research Topics on Multiple Criteria Decision Making: 20th International Conference, MCDM 2009, Chengdu/Jiuzhaigou, Proceedings (pp. 824-832). (Communications in Computer and Information Science; Vol. 35). https://doi.org/10.1007/978-3-642-02298-2_119

Castro, Carlos ; Crawford, Broderick ; Monfroy, Eric. / A genetic local search algorithm for the multiple optimisation of the balanced academic curriculum problem. Cutting-Edge Research Topics on Multiple Criteria Decision Making: 20th International Conference, MCDM 2009, Chengdu/Jiuzhaigou, Proceedings. 2009. pp. 824-832 (Communications in Computer and Information Science).

@inproceedings{4e54c30edcbf4006a7b858b8ccf3c5cc,

title = "A genetic local search algorithm for the multiple optimisation of the balanced academic curriculum problem",

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.",

author = "Carlos Castro and Broderick Crawford and Eric Monfroy",

year = "2009",

doi = "10.1007/978-3-642-02298-2_119",

language = "English",

isbn = "9783642022975",

series = "Communications in Computer and Information Science",

pages = "824--832",

booktitle = "Cutting-Edge Research Topics on Multiple Criteria Decision Making",

}

Castro, C, Crawford, B & Monfroy, E 2009, A genetic local search algorithm for the multiple optimisation of the balanced academic curriculum problem. in Cutting-Edge Research Topics on Multiple Criteria Decision Making: 20th International Conference, MCDM 2009, Chengdu/Jiuzhaigou, Proceedings. Communications in Computer and Information Science, vol. 35, pp. 824-832. https://doi.org/10.1007/978-3-642-02298-2_119

A genetic local search algorithm for the multiple optimisation of the balanced academic curriculum problem. / Castro, Carlos; Crawford, Broderick; Monfroy, Eric.

Cutting-Edge Research Topics on Multiple Criteria Decision Making: 20th International Conference, MCDM 2009, Chengdu/Jiuzhaigou, Proceedings. 2009. p. 824-832 (Communications in Computer and Information Science; Vol. 35).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - A genetic local search algorithm for the multiple optimisation of the balanced academic curriculum problem

AU - Castro, Carlos

AU - Crawford, Broderick

AU - Monfroy, Eric

PY - 2009

Y1 - 2009

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=68349148503&partnerID=8YFLogxK

U2 - 10.1007/978-3-642-02298-2_119

DO - 10.1007/978-3-642-02298-2_119

M3 - Conference contribution

AN - SCOPUS:68349148503

SN - 9783642022975

T3 - Communications in Computer and Information Science

SP - 824

EP - 832

BT - Cutting-Edge Research Topics on Multiple Criteria Decision Making

ER -

Castro C, Crawford B, Monfroy E. A genetic local search algorithm for the multiple optimisation of the balanced academic curriculum problem. In Cutting-Edge Research Topics on Multiple Criteria Decision Making: 20th International Conference, MCDM 2009, Chengdu/Jiuzhaigou, Proceedings. 2009. p. 824-832. (Communications in Computer and Information Science). https://doi.org/10.1007/978-3-642-02298-2_119

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

Abstract

Publication series

Access to Document

Other files and links

Fingerprint

Cite this