It is widely acknowledged that some of the most powerful algorithms for graph coloring involve the combination of evolutionary-based methods with exploitative local search-based techniques. This chapter conducts a review and discussion of such methods, principally focussing on the role that recombination plays in this process. In particular we observe that, while in some cases recombination seems to be usefully combining substructures inherited from parents, in other cases it is merely acting as a macro perturbation operator, helping to reinvigorate the search from time to time
Abstract. Recombination is supposed to enable the component characteristics from two parents to be e...
The adaptive memory algorithm (AMA) is a population-based metaheuristics initially developed in 1995...
The maximum happy vertices problem involves taking a simple graph in which several vertices are prec...
It is widely acknowledged that some of the most powerful algorithms for graph coloring involve the c...
It is widely acknowledged that some of the most powerful algorithms for graph coloring involve the c...
We present a diversity-oriented hybrid evolutionary approach for the graph coloring problem. This ap...
International audienceAbstract. We present a hybrid evolutionary algorithm for the graph coloring pr...
We present a hybrid evolutionary algorithm for the graph coloring problem (Evocol). Evocol is based ...
In this paper a new parallel genetic algorithm for coloring graph vertices is presented. In the algo...
. This paper presents a new genetic local search algorithm for the graph coloring problem. The algor...
Abstract — This work studies and compares the effects on performance of local dominance and local re...
This paper examines the best current algorithm for solving the Chromatic Number Problem, due to Gali...
This paper presents the results of an experimental investigation on solving graph coloring problems ...
One of the central problems in computational biology is the reconstruction of evolutionary histories...
In this paper a new parallel genetic algorithm for coloring graph vertices is presented. In the algo...
Abstract. Recombination is supposed to enable the component characteristics from two parents to be e...
The adaptive memory algorithm (AMA) is a population-based metaheuristics initially developed in 1995...
The maximum happy vertices problem involves taking a simple graph in which several vertices are prec...
It is widely acknowledged that some of the most powerful algorithms for graph coloring involve the c...
It is widely acknowledged that some of the most powerful algorithms for graph coloring involve the c...
We present a diversity-oriented hybrid evolutionary approach for the graph coloring problem. This ap...
International audienceAbstract. We present a hybrid evolutionary algorithm for the graph coloring pr...
We present a hybrid evolutionary algorithm for the graph coloring problem (Evocol). Evocol is based ...
In this paper a new parallel genetic algorithm for coloring graph vertices is presented. In the algo...
. This paper presents a new genetic local search algorithm for the graph coloring problem. The algor...
Abstract — This work studies and compares the effects on performance of local dominance and local re...
This paper examines the best current algorithm for solving the Chromatic Number Problem, due to Gali...
This paper presents the results of an experimental investigation on solving graph coloring problems ...
One of the central problems in computational biology is the reconstruction of evolutionary histories...
In this paper a new parallel genetic algorithm for coloring graph vertices is presented. In the algo...
Abstract. Recombination is supposed to enable the component characteristics from two parents to be e...
The adaptive memory algorithm (AMA) is a population-based metaheuristics initially developed in 1995...
The maximum happy vertices problem involves taking a simple graph in which several vertices are prec...