Add to ORKGAbstract – The article deals with the properties of linear combinatorial optimization problems on a set of arrangements under probabilistic uncertainty. The statement of the problem, considering the possibility of stochastic uncertainty of the initial data, is considered. The properties of the formulated stochastic problems are explored
We consider general combinatorial optimization problems that can be formulated as minimizing the wei...
Many planning problems involve choosing a set of optimal decisions for a system in the face of uncer...
We study two-stage, finite-scenario stochastic versions of several combinatorial optimization proble...
This paper briefly describes three well-established frameworks for handling uncertainty in optimizat...
The paper deals with the solution of a stochastic optimization problem under incomplete information....
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer...
Given subsets of uncertain values, we study the problem of identifying the subset of minimum total v...
\u3cp\u3eThis paper presents an investigation on the computational complexity of stochastic optimiza...
In this dissertation, we investigate two basic planning problems in Operations Research, non-probabi...
<p>The focus of this thesis is on the design and analysis of algorithms for basic problems in Stocha...
summary:The aim of this paper is to present some ideas how to relax the notion of the optimal soluti...
Abstract. This paper presents an investigation on the computational complexity of stochastic optimiz...
We present a general framework for stochastic online maximization problems with combinatorial feasib...
Stochastic Optimization Algorithms have become essential tools in solving a wide range of difficult ...
In practical problem situations data are usually inherently unreliable. A mathematical representatio...
We consider general combinatorial optimization problems that can be formulated as minimizing the wei...
Many planning problems involve choosing a set of optimal decisions for a system in the face of uncer...
We study two-stage, finite-scenario stochastic versions of several combinatorial optimization proble...
This paper briefly describes three well-established frameworks for handling uncertainty in optimizat...
The paper deals with the solution of a stochastic optimization problem under incomplete information....
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer...
Given subsets of uncertain values, we study the problem of identifying the subset of minimum total v...
\u3cp\u3eThis paper presents an investigation on the computational complexity of stochastic optimiza...
In this dissertation, we investigate two basic planning problems in Operations Research, non-probabi...
<p>The focus of this thesis is on the design and analysis of algorithms for basic problems in Stocha...
summary:The aim of this paper is to present some ideas how to relax the notion of the optimal soluti...
Abstract. This paper presents an investigation on the computational complexity of stochastic optimiz...
We present a general framework for stochastic online maximization problems with combinatorial feasib...
Stochastic Optimization Algorithms have become essential tools in solving a wide range of difficult ...
In practical problem situations data are usually inherently unreliable. A mathematical representatio...
We consider general combinatorial optimization problems that can be formulated as minimizing the wei...
Many planning problems involve choosing a set of optimal decisions for a system in the face of uncer...
We study two-stage, finite-scenario stochastic versions of several combinatorial optimization proble...