Applying minimum-risk criterion to stochastic hub location problems

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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.




Zhai, H., Liu, Y., & Chen, W. (2012). Applying minimum-risk criterion to stochastic hub location problems. In Procedia Engineering (Vol. 29, pp. 2313–2321).

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