This article analyses a counting process associated with a stochastic process arising in global optimisation. Backtracking adaptive search (BAS) is a theoretical stochastic global optimisation algorithm modelling the temporary acceptance of solutions of lower quality. BAS generalises the pure adaptive search and hesitant adaptive search algorithms, whose full search duration distributions are known. This article gives the exact expected search duration for backtracking adaptive search.14 page(s
Consider an infinite binary search tree in which the branches have independent random costs. Suppose...
In this paper, a new random search technique which facilitates the determination of the global minim...
When a deterministic algorithm for finding the minimum of a function C on a set Ω is em-ployed it ma...
Backtracking adaptive search is an optimisation algorithm which generalises pure adaptive search and...
A useful measure of quality of a global optimisation algorithm such as simulated annealing is the le...
How long should we run a stochastic global optimisation algorithm such as simulated annealing? How s...
This thesis addresses aspects of stochastic algorithms for the solution of global optimisation probl...
Real-time heuristic search algorithms are suitable for situated agents that need to make their decis...
Abstract- In the real world scenario we come across the problem of optimization a number of times. F...
In this paper we develop a methodology for defining stopping rules in a general class of global rand...
It is often necessary, in scientific or everyday life problems, to find a randomly hidden target. Wh...
This paper addresses the following question: what is the essential difference between stochastic loc...
In this paper, we propose a formulation of the spatial search problem, where a mobile searching agen...
This paper addresses the following question: what is the es-sential difference between stochastic lo...
PACS. 87.23.-n – Ecology and evolution. PACS. 05.40.-a – Fluctuation phenomena, random processes, no...
Consider an infinite binary search tree in which the branches have independent random costs. Suppose...
In this paper, a new random search technique which facilitates the determination of the global minim...
When a deterministic algorithm for finding the minimum of a function C on a set Ω is em-ployed it ma...
Backtracking adaptive search is an optimisation algorithm which generalises pure adaptive search and...
A useful measure of quality of a global optimisation algorithm such as simulated annealing is the le...
How long should we run a stochastic global optimisation algorithm such as simulated annealing? How s...
This thesis addresses aspects of stochastic algorithms for the solution of global optimisation probl...
Real-time heuristic search algorithms are suitable for situated agents that need to make their decis...
Abstract- In the real world scenario we come across the problem of optimization a number of times. F...
In this paper we develop a methodology for defining stopping rules in a general class of global rand...
It is often necessary, in scientific or everyday life problems, to find a randomly hidden target. Wh...
This paper addresses the following question: what is the essential difference between stochastic loc...
In this paper, we propose a formulation of the spatial search problem, where a mobile searching agen...
This paper addresses the following question: what is the es-sential difference between stochastic lo...
PACS. 87.23.-n – Ecology and evolution. PACS. 05.40.-a – Fluctuation phenomena, random processes, no...
Consider an infinite binary search tree in which the branches have independent random costs. Suppose...
In this paper, a new random search technique which facilitates the determination of the global minim...
When a deterministic algorithm for finding the minimum of a function C on a set Ω is em-ployed it ma...