Add to ORKGAccelerated probabilistic modeling algorithms, presenting stochastic local search (SLS) technique, are considered. General algorithm scheme and specific combinatorial optimization method, using “golden section” rule (GS-method), are given. Convergence rates using Markov chains are received. An overview of current combinatorial optimization techniques is presented
We present some typical algorithms used for finding global minimum/maximum of a function defined on...
Many stochastic local search (SLS) methods rely on the manipulation of single solutions at each of t...
This thesis addresses aspects of stochastic algorithms for the solution of global optimisation probl...
The main objective of this paper is to provide a state-of-the-art review, analyze and discuss stocha...
Stochastic local search (SLS) algorithms are among the most prominent and successful techniques for ...
In this chapter, we give an overview of the main concepts underlying the stochastic local search (SL...
[1] Sergienko I.V., Kaspshitskaya M.F. Models and methods solving combinatorial optimization problem...
Stochastic Local Search algorithms (SLS) are a class of methods used to tacklehard combinatorial opt...
AbstractThis paper analyzes the performance of local search algorithms (guided by the best-to-date s...
Combinatorial optimisation problems are an important and well-studied class of problems, with applic...
This book presents the main methodological and theoretical developments in stochastic global optimiz...
Stochastic local search (SLS) algorithms are typically composed of a number of different components,...
We present some typical algorithms used for finding global minimum/ maximum of a function defined on...
AbstractGeneralized hill climbing (GHC) algorithms provide a general local search strategy to addres...
International audienceMany stochastic local search (SLS) methods rely on the manipulation of single ...
We present some typical algorithms used for finding global minimum/maximum of a function defined on...
Many stochastic local search (SLS) methods rely on the manipulation of single solutions at each of t...
This thesis addresses aspects of stochastic algorithms for the solution of global optimisation probl...
The main objective of this paper is to provide a state-of-the-art review, analyze and discuss stocha...
Stochastic local search (SLS) algorithms are among the most prominent and successful techniques for ...
In this chapter, we give an overview of the main concepts underlying the stochastic local search (SL...
[1] Sergienko I.V., Kaspshitskaya M.F. Models and methods solving combinatorial optimization problem...
Stochastic Local Search algorithms (SLS) are a class of methods used to tacklehard combinatorial opt...
AbstractThis paper analyzes the performance of local search algorithms (guided by the best-to-date s...
Combinatorial optimisation problems are an important and well-studied class of problems, with applic...
This book presents the main methodological and theoretical developments in stochastic global optimiz...
Stochastic local search (SLS) algorithms are typically composed of a number of different components,...
We present some typical algorithms used for finding global minimum/ maximum of a function defined on...
AbstractGeneralized hill climbing (GHC) algorithms provide a general local search strategy to addres...
International audienceMany stochastic local search (SLS) methods rely on the manipulation of single ...
We present some typical algorithms used for finding global minimum/maximum of a function defined on...
Many stochastic local search (SLS) methods rely on the manipulation of single solutions at each of t...
This thesis addresses aspects of stochastic algorithms for the solution of global optimisation probl...