منابع مشابه
Online stochastic optimization under time constraints
This paper considers online stochastic combinatorial optimization problems where uncertainties, i.e., which requests come and when, are characterized by distributions that can be sampled and where time constraints severely limit the number of offline optimizations which can be performed at decision time and/or in between decisions. It proposes online stochastic algorithms that combine the frame...
متن کاملStochastic Combinatorial Optimization under Probabilistic Constraints
In this paper, we present approximation algorithms for combinatorial optimization problems under probabilistic constraints. Specifically, we focus on stochastic variants of two important combinatorial optimization problems: the k-center problem and the set cover problem, with uncertainty characterized by a probability distribution over set of points or elements to be covered. We consider these ...
متن کاملElectric Company Portfolio Optimization Under Interval Stochastic Dominance Constraints
This paper addresses the problem of market risk management for a company in the electricity industry. When dealing with corporate volumetric exposure, there is a need for a methodology that helps to manage the aggregate risks in energy markets. The originality of the approach presented lies in the use of intervals to formulate a specific portfolio optimization problem under stochastic dominance...
متن کاملNew Formulations for Optimization under Stochastic Dominance Constraints
Stochastic dominance constraints allow a decision-maker to manage risk in an optimization setting by requiring their decision to yield a random outcome which stochastically dominates a reference random outcome. We present new integer and linear programming formulations for optimization under first and second-order stochastic dominance constraints, respectively. These formulations are more compa...
متن کاملRegrets Only! Online Stochastic Optimization under Time Constraints
This paper considers online stochastic optimization problems where time constraints severely limit the number of offline optimizations which can be performed at decision time and/or in between decisions. It proposes a novel approach which combines the salient features of the earlier approaches: the evaluation of every decision on all samples (expectation) and the ability to avoid distributing t...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Stochastic Processes and their Applications
سال: 2001
ISSN: 0304-4149
DOI: 10.1016/s0304-4149(00)00089-2