Mobile ad-hoc networks: a new stochastic second-order cone programming approach Serie Ricerca Mobile ad-hoc networks: a new stochastic second-order cone programming approach Abstract. We study the semidefinite stochastic location-aided routing (SLAR) model described in Ariyawansa and Zhu (2006) [2] and in Zhu, Zhang, and Patel (2007) [16]. We propose a modification of their model to exploit the...

Decomposition has proved to be one of the more effective tools for the solution of large-scale problems, especially those arising in stochastic programming. A decomposition method with wide applicability is Benders’ decomposition, and has been applied to both stochastic programming, as well as integer programming problems. However, this method of decomposition relies on convexity of the value f...

Abstract: The most important character within the optimization problem is the uncertainty of the future returns. To handle such problems, we utilize probabilistic methods alongside with optimization techniques. We develop single stage and two stage stochastic programming with recourse with the objective is to minimize the maximum downside semi deviation. We use the so-called “Here-and-Now” appr...

We show that a number of problems in Artificial Intelligence can be seen as Stochastic Constraint Optimization Problems (SCOPs): problems that have both a stochastic and a constraint optimization component. We argue that these problems can be modeled in a new language, SC-ProbLog, that combines a generic Probabilistic Logic Programming (PLP) language, ProbLog, with stochastic constraint optimiz...

We present a study of the two-stage stochastic view selection problem in database management systems. The objective is to minimize processing times of the given queries subject to a storage limit. We assume that the queries are given in two or more workloads. We propose a two-stage stochastic programming (SP) model for this problem and study the structure and properties of its extensive form, w...