Humanitarian organizations pre-position relief items in pre-disaster and distribute them to the affected areas in post-disaster. Improper planning of emergency operations causes more deaths in post-disaster. In this paper, the problem of relief item pre-positioning and multi-period distribution planning is addressed considering lateral transhipment among distribution centres to improve the effi...

Stochastic programming problems arise in many practical situations. In general, the deterministic equivalents of these problems can be very large and may not be solvable directly by general-purpose optimization approaches. For the particular case of two-stage stochastic programs, we consider decomposition approaches akin to a regularized L-shaped method that can handle inexactness in the subpro...

Some recent developments in the area of risk aversion in stochastic integer programming are surveyed. After a discussion of modeling guidelines and resulting mean-risk stochastic integer programs emphasis is placed on structural properties of these optimization problems and on algoritms for their solution. Bibliographical notes conclude the paper.

In applications of stochastic programming, optimization of the expected outcome need not be an acceptable goal. This has been the reason for recent proposals aiming at construction and optimization of more complicated nonlinear risk objectives. We will survey various approaches to risk quantification and optimization mainly in the framework of static and two-stage stochastic programs and commen...

In this paper we consider the Two-stage Stochastic Linear Programming (TSLP) problem with continuous random parameters. A common way to approximate the TSLP problem, generally intractable, is to discretize the random parameters into scenarios. Another common approximation only considers the expectation of the parameters, that is, the expected scenario. In this paper we introduce the conditional...