An Approach with Nested Partition for Resource-Constrained Project Scheduling Problem

Zhen-yuan Liu () and Wen-min Yu ()
Additional contact information
Zhen-yuan Liu: Huazhong University of Science and Technology
Wen-min Yu: Huazhong University of Science and Technology

Chapter Chapter 78 in The 19th International Conference on Industrial Engineering and Engineering Management, 2013, pp 737-748 from Springer

Abstract: Abstract A time-based nested partition (NP) approach is proposed to solve resource-constrained project scheduling problem (RCPSP) in this paper. In iteration, one activity is selected as the base point of which the finish time interval calculated by CPM is divided into two parts to form two subregions on the basis of the promising region of the last iteration. Then sampling is taken in both subregions and the surrounding region to determine the promising region and aggregate the other as the surrounding region of this iteration so that whether the backtracking or the moving operation being performed is determined. Double justification is also performed in iteration to improve the results. The results of numerical tests on PSPLIB show the effectiveness and time-efficient of the proposed NP method.

Keywords: Double justification; Nested partition; RCPSP; Sampling (search for similar items in EconPapers)
Date: 2013
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

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:sprchp:978-3-642-38391-5_78

Ordering information: This item can be ordered from
http://www.springer.com/9783642383915

DOI: 10.1007/978-3-642-38391-5_78

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().