The goal of exploration to produce diverse search points throughout the search space can be countered by the goal of selection to focus search around the fittest current solution(s). In the limit, if all exploratory search points are rejected by selection, then the behaviour of the metaheuristic will be equivalent to one which performs no exploration at all (e.g. hill climbing). The effects of selection on exploration are clearly important, but our review of the literature indicates limited coverage. To address this deficit, we introduce new experiments which can specifically highlight the occurrence of “failed exploration” and its effects through selection that can trap a metaheuristic in a less promising part of the search space. We subse...
Evolutionary algorithms are playing an increasingly important role as search methods in cognitive sc...
Differential Evolution (DE) is a tool for efficient optimisation, and it belongs to the class of evo...
Particle Swarm Optimization (PSO), an evolutionary algorithm for optimization is extended to determ...
The goal of exploration to produce diverse search points throughout the search space can be countere...
Random walks are a useful modeling tool for stochastic processes. The addition of model features (e....
Fitness landscapes facilitate the analysis of optimisation problems in a detailed, yet intuitive man...
In this article we propose a formalisation of the concept of exploration performed by metaheuristics...
Evolutionary algorithms are effective general-purpose techniques for solving optimization problems. ...
Exploration and exploitation are analyzed in Particle Swarm Optimization (PSO) through a set of expe...
Two factors affect the effectiveness of exploration, the bias introduced by selection and the concur...
We use evolutionary computation (EC) to automatically find problems which demonstrate the strength a...
The size, scope and variety of the experimental analyses of metaheuristics has increased in recent y...
Many methods for multi-objective optimisation exist, and there are multiple studies in which their p...
We use evolutionary computation (EC) to automatically find problems which demonstrate the strength a...
Particle Swarm Optimization (PSO) is a popular nature-inspired meta-heuristic for solving continuous...
Evolutionary algorithms are playing an increasingly important role as search methods in cognitive sc...
Differential Evolution (DE) is a tool for efficient optimisation, and it belongs to the class of evo...
Particle Swarm Optimization (PSO), an evolutionary algorithm for optimization is extended to determ...
The goal of exploration to produce diverse search points throughout the search space can be countere...
Random walks are a useful modeling tool for stochastic processes. The addition of model features (e....
Fitness landscapes facilitate the analysis of optimisation problems in a detailed, yet intuitive man...
In this article we propose a formalisation of the concept of exploration performed by metaheuristics...
Evolutionary algorithms are effective general-purpose techniques for solving optimization problems. ...
Exploration and exploitation are analyzed in Particle Swarm Optimization (PSO) through a set of expe...
Two factors affect the effectiveness of exploration, the bias introduced by selection and the concur...
We use evolutionary computation (EC) to automatically find problems which demonstrate the strength a...
The size, scope and variety of the experimental analyses of metaheuristics has increased in recent y...
Many methods for multi-objective optimisation exist, and there are multiple studies in which their p...
We use evolutionary computation (EC) to automatically find problems which demonstrate the strength a...
Particle Swarm Optimization (PSO) is a popular nature-inspired meta-heuristic for solving continuous...
Evolutionary algorithms are playing an increasingly important role as search methods in cognitive sc...
Differential Evolution (DE) is a tool for efficient optimisation, and it belongs to the class of evo...
Particle Swarm Optimization (PSO), an evolutionary algorithm for optimization is extended to determ...