Resource allocation in robust scheduling

Pang Nansheng and Meng Qichen

Journal of the Operational Research Society, 2023, vol. 74, issue 1, 125-142

Abstract: A robust project scheduling based on resource flow network can prevent new resource contentions from adjustments when encountering the uncertainties during the execution. However, the resource flow network will increase the interdependencies of the activities and lower the robustness of the schedule. For this reason, we propose a heuristic resource allocation algorithm of maximizing the use of precedence relation (MaxPR) to optimize the resource allocation schedule. Our contributions are as follows: first, this paper presents a two-stage algorithm to allocate resources. In Stage 1, the activity pairs with precedence relation can be divided into two categories, zero-lag relation and relation with time-lag. Second, the strategy of unavoidable arcs is adopted to allocate resources to the activity pairs without precedence relation in Stage 2. Third, it is also proved by simulation experiments that MaxPR and its multiple allocation strategies will generate less additional constraints compared with other six algorithms. It can also adapt to various network structures, showing the concision and feasibility of this algorithm.

Date: 2023
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/01605682.2022.2029593 (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:taf:tjorxx:v:74:y:2023:i:1:p:125-142

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/tjor20

DOI: 10.1080/01605682.2022.2029593

Access Statistics for this article

Journal of the Operational Research Society is currently edited by Tom Archibald

More articles in Journal of the Operational Research Society from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().