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EVOW
2008
Springer
13 years 6 months ago
Improving Metaheuristic Performance by Evolving a Variable Fitness Function
In this paper we study a complex real world workforce scheduling problem. We apply constructive search and variable neighbourhood search (VNS) metaheuristics and enhance these meth...
Keshav P. Dahal, Stephen Remde, Peter I. Cowling, ...
LION
2007
Springer
139views Optimization» more  LION 2007»
13 years 10 months ago
Evolution of Fitness Functions to Improve Heuristic Performance
In this paper we introduce the variable fitness function which can be used to control the search direction of any search based optimisation heuristic where more than one objective ...
Stephen Remde, Peter I. Cowling, Keshav P. Dahal, ...
SOCO
2010
Springer
13 years 2 months ago
Evaluating a local genetic algorithm as context-independent local search operator for metaheuristics
Local genetic algorithms have been designed with the aim of providing effective intensification. One of their most outstanding features is that they may help classical local searc...
Carlos García-Martínez, Manuel Lozan...
CEC
2008
IEEE
13 years 10 months ago
Fitness functions for the unconstrained evolution of digital circuits
— This work is part of a project that aims to develop and operate integrated evolvable hardware systems using unconstrained evolution. Experiments are carried out on an evolvable...
Tüze Kuyucu, Martin Trefzer, Andrew J. Greens...
GECCO
2009
Springer
130views Optimization» more  GECCO 2009»
13 years 9 months ago
Neutrality and variability: two sides of evolvability in linear genetic programming
The notion of evolvability has been put forward to describe the“core mechanism”of natural and artificial evolution. Recently, studies have revealed the influence of the envi...
Ting Hu, Wolfgang Banzhaf