A new genetic algorithm for resource constrained project scheduling

Yassaman Mohsenin, Hesham H Ali

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

Abstract

The Project Scheduling Problem has attracted the attention of researchers for years. Much of this research has been conducted in the Resource Constrained Project Scheduling Problem (RCPSP). The goal of this paper is to define new Genetic Algorithms Operators for a new a model of Resource Constrained Project Scheduling Problem with heterogeneous resources (operators). The model better resembles real-world projects and has more flexibility than previous models for manpower scheduling. Most RCPSP research uses Finish Time as a measure of the fitness of a solution. In this model the combination of Quality and Finish Time will be used. The goal will be to maximize the Quality and minimize the Finish Time. To solve the problem, the model will use Genetic Algorithms. New Crossover and Mutation operators will be implemented. These operators will attempt to create children with the same or higher Quality than their parents and will add the children the solution pool.

Original languageEnglish (US)
Title of host publicationProceedings of the IASTED International Conference on Artificial Intelligence and Applications, AIA 2008
Pages307-313
Number of pages7
StatePublished - Dec 1 2008
EventIASTED International Conference on Artificial Intelligence and Applications, AIA 2008 - Innsbruck, Austria
Duration: Feb 13 2008Feb 15 2008

Publication series

NameProceedings of the IASTED International Conference on Artificial Intelligence and Applications, AIA 2008

Conference

ConferenceIASTED International Conference on Artificial Intelligence and Applications, AIA 2008
CountryAustria
CityInnsbruck
Period2/13/082/15/08

Fingerprint

Genetic algorithms
Scheduling
Mathematical operators

Keywords

  • Genetic algorithms
  • Resource allocation
  • Scheduling

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications

Cite this

Mohsenin, Y., & Ali, H. H. (2008). A new genetic algorithm for resource constrained project scheduling. In Proceedings of the IASTED International Conference on Artificial Intelligence and Applications, AIA 2008 (pp. 307-313). (Proceedings of the IASTED International Conference on Artificial Intelligence and Applications, AIA 2008).

A new genetic algorithm for resource constrained project scheduling. / Mohsenin, Yassaman; Ali, Hesham H.

Proceedings of the IASTED International Conference on Artificial Intelligence and Applications, AIA 2008. 2008. p. 307-313 (Proceedings of the IASTED International Conference on Artificial Intelligence and Applications, AIA 2008).

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

Mohsenin, Y & Ali, HH 2008, A new genetic algorithm for resource constrained project scheduling. in Proceedings of the IASTED International Conference on Artificial Intelligence and Applications, AIA 2008. Proceedings of the IASTED International Conference on Artificial Intelligence and Applications, AIA 2008, pp. 307-313, IASTED International Conference on Artificial Intelligence and Applications, AIA 2008, Innsbruck, Austria, 2/13/08.
Mohsenin Y, Ali HH. A new genetic algorithm for resource constrained project scheduling. In Proceedings of the IASTED International Conference on Artificial Intelligence and Applications, AIA 2008. 2008. p. 307-313. (Proceedings of the IASTED International Conference on Artificial Intelligence and Applications, AIA 2008).
Mohsenin, Yassaman ; Ali, Hesham H. / A new genetic algorithm for resource constrained project scheduling. Proceedings of the IASTED International Conference on Artificial Intelligence and Applications, AIA 2008. 2008. pp. 307-313 (Proceedings of the IASTED International Conference on Artificial Intelligence and Applications, AIA 2008).
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