Evolutionary algorithms have been shown to be very successful for a wide range of NP-hard combinatorial optimization problems. We investigate the NP-hard problem of computing a spanning tree that has a maximal number of leaves by evolutionary algorithms in the context of fixed parameter tractability (FPT) where the maximum number of leaves is the parameter under consideration. Our results show that simple evolutionary algorithms working with an edge-set encoding are confronted with local optima whose size of the inferior neighborhood grows with the value of an optimal solution. Investigating two common mutation operators, we show that an operator related to spanning tree problems leads to an FPT running time in contrast to a general mutatio...
A major challenge to solving multiobjective optimization problems is to capture possibly all the (re...
AbstractRandomized search heuristics, among them randomized local search and evolutionary algorithms...
In the framework of parameterized complexity, exploring how one parameter affects the complexity of ...
Evolutionary algorithms are applied to problems that are not well understood as well as to problems ...
The Minimum Spanning Tree problem is a well-known combinatorial optimization problem, which has attr...
The features of an evolutionary algorithm that most determine its performance are the coding by whic...
Many graph problems seek subgraphs of minimum weight that satisfy the problems’ constraints. Example...
Bi-level optimisation problems have gained increasing interest in the field of combinatorial optimis...
In many applications of evolutionary algorithms the computational cost of applying operators and sto...
The problem of computing spanning trees along with specific constraints has been studied in many for...
We prove that the NP-hard problem of finding in an undirected graph G a spanning tree with a maximum...
Bi-level optimisation problems have gained increasing inter- est in the field of combinatorial optim...
Randomized search heuristics, among them randomized local search and evolutionary algorithms, are ap...
In the framework of parameterized complexity, exploring how one parameter affects the complexity of ...
AbstractGiven an undirected graph with n vertices, the Maximum Leaf Spanning Tree problem is to find...
A major challenge to solving multiobjective optimization problems is to capture possibly all the (re...
AbstractRandomized search heuristics, among them randomized local search and evolutionary algorithms...
In the framework of parameterized complexity, exploring how one parameter affects the complexity of ...
Evolutionary algorithms are applied to problems that are not well understood as well as to problems ...
The Minimum Spanning Tree problem is a well-known combinatorial optimization problem, which has attr...
The features of an evolutionary algorithm that most determine its performance are the coding by whic...
Many graph problems seek subgraphs of minimum weight that satisfy the problems’ constraints. Example...
Bi-level optimisation problems have gained increasing interest in the field of combinatorial optimis...
In many applications of evolutionary algorithms the computational cost of applying operators and sto...
The problem of computing spanning trees along with specific constraints has been studied in many for...
We prove that the NP-hard problem of finding in an undirected graph G a spanning tree with a maximum...
Bi-level optimisation problems have gained increasing inter- est in the field of combinatorial optim...
Randomized search heuristics, among them randomized local search and evolutionary algorithms, are ap...
In the framework of parameterized complexity, exploring how one parameter affects the complexity of ...
AbstractGiven an undirected graph with n vertices, the Maximum Leaf Spanning Tree problem is to find...
A major challenge to solving multiobjective optimization problems is to capture possibly all the (re...
AbstractRandomized search heuristics, among them randomized local search and evolutionary algorithms...
In the framework of parameterized complexity, exploring how one parameter affects the complexity of ...