A New Genetic Algorithm for the RCPSP in Large Scale

Hossein Zoulfaghari, Javad Nematian, Nader Mahmoudi and Mehdi Khodabandeh
Additional contact information
Hossein Zoulfaghari: Department of Industrial Engineering, University of Tabriz, Tabriz, Iran
Javad Nematian: Department of Industrial Engineering, University of Tabriz, Tabriz, Iran
Nader Mahmoudi: Department of Industrial Engineering, University of Tabriz, Tabriz, Iran
Mehdi Khodabandeh: Department of Industrial Engineering, University of Tabriz, Tabriz, Iran

International Journal of Applied Evolutionary Computation (IJAEC), 2013, vol. 4, issue 2, 29-40

Abstract: The Resource Constrained Project Scheduling Problem (RCPSP) is a well-studied academic problem that has been shown to be well suited to optimization via Genetic Algorithms (GA). In this paper, a new method will be designed that would be able to solve RCPSP. This research area is very common in industry especially when a set of activities needs to be finished as soon as possible subject to two sets of constraints, precedence constraints and resource constraints. The presented algorithm in this paper is used to solve large scale RCPSP and improves solutions. Finally, for comparing, results are reported for the most famous classical problems that are taken from PSPLIB.

Date: 2013
References: Add references at CitEc
Citations:

Downloads: (external link)
http://services.igi-global.com/resolvedoi/resolve. ... 4018/jaec.2013040103 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:igg:jaec00:v:4:y:2013:i:2:p:29-40

Access Statistics for this article

International Journal of Applied Evolutionary Computation (IJAEC) is currently edited by Sukhpal Singh Gill

More articles in International Journal of Applied Evolutionary Computation (IJAEC) from IGI Global
Bibliographic data for series maintained by Journal Editor ().