A Competitive Heuristic Solution Technique for Resource-Constrained Project Scheduling

Pilar Tormos () and Antonio Lova ()

Annals of Operations Research, 2001, vol. 102, issue 1, 65-81

Abstract: In this work a new heuristic solution technique for the Resource-Constrained Project Scheduling Problem (RCPSP) is proposed. This technique is a hybrid multi-pass method that combines random sampling procedures with a backward–forward method. The impact of each component of the algorithm is evaluated through a step-wise computational analysis which in addition permits the value of their parameters to be specified. Furthermore, the performance of the new technique is evaluated against the best currently available heuristics using a well known set of instances. The results obtained point out that the new technique greatly outperforms both the heuristics and metaheuristics currently available for the RCPSP being thus competitive with the best heuristic solution techniques for this problem. Copyright Kluwer Academic Publishers 2001

Keywords: project management; resource-constrained project scheduling; random sampling; backward–forward (search for similar items in EconPapers)
Date: 2001
References: Add references at CitEc
Citations: View citations in EconPapers (32)

Downloads: (external link)
http://hdl.handle.net/10.1023/A:1010997814183 (text/html)
Access to full text is restricted to subscribers.

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:spr:annopr:v:102:y:2001:i:1:p:65-81:10.1023/a:1010997814183

Ordering information: This journal article can be ordered from
http://www.springer.com/journal/10479

DOI: 10.1023/A:1010997814183

Access Statistics for this article

Annals of Operations Research is currently edited by Endre Boros

More articles in Annals of Operations Research from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().