The problem of generating a random sample over a level set, called Uniform Covering, is considered. A variant is discussed of an algorithm known as Pure Adaptive Search which is a global optimisation ideal with a desirable complexity. The algorithm of Uniform Covering by Probabilistic Rejection is discussed as an approach to the practical realisation of PAS. Consequences for the complexity and practical performance in comparison to other algorithms are illustrate
Any global minimization algorithm is made by several local searches performed sequentially. In the c...
This dissertation is motivated by the problem of finding a global minimizer or a feasible argument f...
The typical difficulty of various NP-hard problems varies with simple parameters describing their st...
The problem of generating a random sample over a level set, called Uniform Covering, is considered. ...
The Pure Adaptive Search (PAS) algorithm for global optimization yields a sequence of points, each o...
Several Markov chain sampling algorithms, including the Hit-and-Run algorithm, are unified within th...
Controlled Random Search (CRS) is a simple population based algorithm which despite its attractivene...
In this paper, a new random search technique which facilitates the determination of the global minim...
A high number of discrete optimization problems, including Vertex Cover, Set Cover or Feedback Verte...
Conventional random search techniques take a lot of time to reach optimum-like solutions. Thus, rand...
Absiraci-Fixed step size random search for minimization of functions of several parameters is descri...
The main aim of randomized search heuristics is to produce good approximations of optimal solutions ...
In a general combinatorial search problem with binary tests we are given a set of elements and a hyp...
The main aim of randomized search heuristics is to produce good approximations of optimal solutions ...
A combination of the 16th International Conference on Genetic Algorithms (ICGA) and the 12th Annual ...
Any global minimization algorithm is made by several local searches performed sequentially. In the c...
This dissertation is motivated by the problem of finding a global minimizer or a feasible argument f...
The typical difficulty of various NP-hard problems varies with simple parameters describing their st...
The problem of generating a random sample over a level set, called Uniform Covering, is considered. ...
The Pure Adaptive Search (PAS) algorithm for global optimization yields a sequence of points, each o...
Several Markov chain sampling algorithms, including the Hit-and-Run algorithm, are unified within th...
Controlled Random Search (CRS) is a simple population based algorithm which despite its attractivene...
In this paper, a new random search technique which facilitates the determination of the global minim...
A high number of discrete optimization problems, including Vertex Cover, Set Cover or Feedback Verte...
Conventional random search techniques take a lot of time to reach optimum-like solutions. Thus, rand...
Absiraci-Fixed step size random search for minimization of functions of several parameters is descri...
The main aim of randomized search heuristics is to produce good approximations of optimal solutions ...
In a general combinatorial search problem with binary tests we are given a set of elements and a hyp...
The main aim of randomized search heuristics is to produce good approximations of optimal solutions ...
A combination of the 16th International Conference on Genetic Algorithms (ICGA) and the 12th Annual ...
Any global minimization algorithm is made by several local searches performed sequentially. In the c...
This dissertation is motivated by the problem of finding a global minimizer or a feasible argument f...
The typical difficulty of various NP-hard problems varies with simple parameters describing their st...