In this article we propose a formalisation of the concept of exploration performed by metaheuristics. In particular, we define and test a method for studying this aspect regardless of the specific approach implemented. Understanding the behaviour of metaheuristics is important for being able to boost their results. Measuring the exploration performed may help increase this understanding. We propose an experimental analysis to show how the measure of exploration defined may be used to this aim. We quantify the different level of exploration implied by different parameter settings in an ant colony optimisation and in a genetic algorithm for the travelling salesman problem. The results suggest that it may be possible to establish a relation be...
This paper proposes a metaheuristic selection technique for controlling the progress of an evolution...
There are numerous optimisation problems for which heuristics are currently the only practical solut...
Metaheuristics is a term for optimization procedures/algorithms that can be applied to a wide range ...
In this article we propose a formalisation of the concept of exploration performed by metaheuristics...
Metaheuristic search algorithms look for solutions that either max-imise or minimise a set of object...
Random walks are a useful modeling tool for stochastic processes. The addition of model features (e....
Developping metaheuristics requires in general a lot of work tuning different parameters. This paper...
“… an excellent book if you want to learn about a number of individual metaheuristics." (U. Aickelin...
Heuristic algorithms are often difficult to analyse theoretically; this holds in particular for adva...
The aim of this work was to compare metaheuristic Ant Colony with other metaheuristics like Simulate...
Ant colony optimization is a meta-heuristic algorithm inspired by the foraging behavior of real ant ...
A specialized thread of metaheuristic research, bordering and often overlapping with Artificial Inte...
The present work introduces the reader to the basic concepts behind the metaheuristics methods and t...
Abstract. Metaheuristics are a class of effective algorithms for optimization prob-lems. A basic imp...
Metaheuristics are randomised search algorithms that are effective at finding "good enough" solution...
This paper proposes a metaheuristic selection technique for controlling the progress of an evolution...
There are numerous optimisation problems for which heuristics are currently the only practical solut...
Metaheuristics is a term for optimization procedures/algorithms that can be applied to a wide range ...
In this article we propose a formalisation of the concept of exploration performed by metaheuristics...
Metaheuristic search algorithms look for solutions that either max-imise or minimise a set of object...
Random walks are a useful modeling tool for stochastic processes. The addition of model features (e....
Developping metaheuristics requires in general a lot of work tuning different parameters. This paper...
“… an excellent book if you want to learn about a number of individual metaheuristics." (U. Aickelin...
Heuristic algorithms are often difficult to analyse theoretically; this holds in particular for adva...
The aim of this work was to compare metaheuristic Ant Colony with other metaheuristics like Simulate...
Ant colony optimization is a meta-heuristic algorithm inspired by the foraging behavior of real ant ...
A specialized thread of metaheuristic research, bordering and often overlapping with Artificial Inte...
The present work introduces the reader to the basic concepts behind the metaheuristics methods and t...
Abstract. Metaheuristics are a class of effective algorithms for optimization prob-lems. A basic imp...
Metaheuristics are randomised search algorithms that are effective at finding "good enough" solution...
This paper proposes a metaheuristic selection technique for controlling the progress of an evolution...
There are numerous optimisation problems for which heuristics are currently the only practical solut...
Metaheuristics is a term for optimization procedures/algorithms that can be applied to a wide range ...