List of notations Preface to the second edition Preface to the first edition 1. Stochastic programming models 2. Two-stage problems 3. Multistage problems 4. Optimization models with probabilistic constraints 5. Statistical inference 6. Risk averse optimization 7. Background material 8. Bibliographical remarks Bibliography Index.

Lectures on Stochastic Programming: Modeling and Theory

Introduction to stochastic programming

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Combinatorial Auctions

Network Optimization: Continuous and Discrete Models

Lecture Notes in Economics and Mathematical Systems

A probabilistic model applied to emergency service vehicle location

Designing robust emergency medical service via stochastic programming

Stochastic integer programming problems under probabilistic constraints are considered. Deterministic equivalent formulations of the original problem are obtained by using p-efficient points of the distribution function of the right hand side vector. A branch and bound solution method is proposed based on a partial enumeration of the set of these points. The numerical experience with the probabilistic lot-sizing problem shows the potential of the solution approach and the efficiency of the algorithms implemented.

A branch and bound method for stochastic integer problems under probabilistic constraints

In a probabilistic set-covering problem the right-hand side is a random binary vector and the covering constraint has to be satisfied with some prescribed probability. We analyze the structure of the set of probabilistically efficient points of binary random vectors, develop methods for their enumeration, and propose specialized branch-and-bound algorithms for probabilistic set-covering problems.

Patrizia Beraldi

Papers

A probabilistic model applied to emergency service vehicle location

Designing robust emergency medical service via stochastic programming

A branch and bound method for stochastic integer problems under probabilistic constraints

The Probabilistic Set-Covering Problem

Rolling-horizon and fix-and-relax heuristics for the parallel machine lot-sizing and scheduling problem with sequence-dependent set-up costs