EconPapers    
Economics at your fingertips  
 

Chance-Constrained Programming Model for Optimal Project Selection and Scheduling

Tian-yi Zhao and Xiao-xia Huang ()
Additional contact information
Tian-yi Zhao: University of Science and Technology Beijing
Xiao-xia Huang: University of Science and Technology Beijing

Chapter Chapter 27 in The 19th International Conference on Industrial Engineering and Engineering Management, 2013, pp 243-250 from Springer

Abstract: Abstract This study discusses the optimizing project selection and scheduling problems. In real life, cash inflows and cash outflows of each project are uncertain, we regard them as stochastic variables consequently. Considering time value of capital, Net present value is used as the standard to measure the projects and introduce chance-constraints to control the uncertainty and formulate the model. According to the logical relationship and the characters of projects, we introduce implicit enumeration algorithm to select appropriate projects and schedule them in a reasonable order. Finally, a numerical example is given to express the thought of the model.

Keywords: Chance-constrained programming; Project selection; Implicit enumeration algorithm (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:978-3-642-38433-2_27

Ordering information: This item can be ordered from
http://www.springer.com/9783642384332

DOI: 10.1007/978-3-642-38433-2_27

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 ().

 
Page updated 2025-04-02
Handle: RePEc:spr:sprchp:978-3-642-38433-2_27