Exact and heuristic methods to solve the parallel machine scheduling problem with multi-processor tasks

Lingxiao Wu and Shuaian Wang

International Journal of Production Economics, 2018, vol. 201, issue C, 26-40

Abstract: This paper studies a special parallel machine scheduling problem where some tasks require more than one machine to process, known as the Parallel Machine Scheduling Problem with Multi-processor Tasks. Two mathematical models and several theoretical properties are proposed for the studied problem. To solve this problem, this paper develops an exact branch and bound algorithm and a heuristic tabu search algorithm. A series of numerical experiments are conducted to test the performance of these solution methods. The computational results show that the solution methods are effective and efficient in solving the problem with different sizes.

Keywords: Scheduling; Parallel machine; Multi-processor tasks; Branch and bound; Tabu search (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0925527318301683
Full text for ScienceDirect subscribers only

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:eee:proeco:v:201:y:2018:i:c:p:26-40

DOI: 10.1016/j.ijpe.2018.04.013

Access Statistics for this article

International Journal of Production Economics is currently edited by Stefan Minner

More articles in International Journal of Production Economics from Elsevier
Bibliographic data for series maintained by Catherine Liu ().