Applying minimum-risk criterion to stochastic hub location problems

12Citations
Citations of this article
20Readers
Mendeley users who have this article in their library.

Abstract

This paper presents a new class of two-stage stochastic hub location (HL) programming problems with minimum-risk criterion, in which uncertain demands are characterized by random vector. Meanwhile we demonstrate that the twostage programming problem is equivalent to a single-stage stochastic P-model. Under mild assumptions, we develop a deterministic binary programming problem by using standardization, which is equivalent to a binary fractional programming problem. Moreover, we show that the relaxation problem of the binary fractional programming problem is a convex programming problem. Taking advantage of branch-and-bound method, we provide a number of experiments to illustrate the efficiency of the proposed modeling idea. © 2011 Published by Elsevier Ltd.

Cite

CITATION STYLE

APA

Zhai, H., Liu, Y., & Chen, W. (2012). Applying minimum-risk criterion to stochastic hub location problems. In Procedia Engineering (Vol. 29, pp. 2313–2321). https://doi.org/10.1016/j.proeng.2012.01.307

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free