Fei, Xin, Gulpinar, Nalan and Branke, Jürgen (2019) Efficient solution selection for two-stage stochastic programs. European Journal of Operational Research, 277 (3). pp. 918-929. doi:10.1016/j.ejor.2019.02.015

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Abstract

Sampling-based stochastic programs are extensively applied in practice. However, the resulting models tend to be computationally challenging. A reasonable number of samples needs to be identified to represent the random data, and a group of approximate models can then be constructed using such a number of samples. These approximate models can produce a set of potential solutions for the original model. In this paper, we consider the problem of allocating a finite computational budget among numerous potential solutions of a two-stage linear stochastic program, which aims to identify the best solution among potential ones by conducting simulation under a given computational budget. We propose a two-stage heuristic approach to solve the computational resource allocation problem. First, we utilise a Wasserstein-based screening rule to remove potentially inferior solutions from the simulation. Next, we use a ranking and selection technique to efficiently collect performance information of the remaining solutions. The performance of our approach is demonstrated through well-known benchmark problems. Results show that our method provides good trade-offs between computational effort and solution performance.

Item Type:	Journal Article
Subjects:	Q Science > Q Science (General) Q Science > QA Mathematics
Divisions:	Faculty of Social Sciences > Warwick Business School
Journal or Publication Title:	European Journal of Operational Research
Publisher:	Elsevier Science BV
ISSN:	0377-2217
Official Date:	19 September 2019
Dates:	Date Event 19 September 2019 Published 12 February 2019 Available 6 February 2019 Accepted 3 November 2018 Modified
Date of first compliant deposit:	6 February 2019
Volume:	277
Number:	3
Page Range:	pp. 918-929
DOI:	10.1016/j.ejor.2019.02.015
Status:	Peer Reviewed
Publication Status:	Published
Access rights to Published version:	Restricted or Subscription Access
Related URLs:	Publisher

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