Many problems from combinatorial optimization are NP-hard, so that exact methods remain inefficient to solve them efficiently. However, metaheuristics are approximation methods known and used for their efficiency. But they often require a lot of parameters, which are very difficult to set in order to provide good performance. As a consequence, a challenging question is to perform such parameter tuning easier, or adaptive. The fitness landscape of given combinatorial optimization problem, based on a search space, a fitness function and a neighborhood relation, allow to characterize the problem structure and make the understanding of the dynamics of search approches possible. This thesis deals with fitness landscape analysis, together with th...
International audienceSolving efficiently complex problems using metaheuristics, and in particular l...
International audienceIn previous work we have introduced a network-based model that abstracts many ...
International audienceIn previous work we have introduced a network-based model that abstracts many ...
Les problèmes d'optimisation combinatoire sont généralement NP-difficiles et les méthodes exactes de...
Les problèmes d'optimisation combinatoire sont généralement NP-difficiles et les méthodes exactes de...
Many combinatorial optimization problems are hard to solve and in many cases, exact approaches are i...
Many combinatorial optimization problems are hard to solve and in many cases, exact approaches are i...
The concept of fitness landscape (or adaptive landscape) was introduce par S. Wright in the field of...
International audienceThis paper presents a new methodology that exploits specific characteristics f...
International audienceThis paper presents a new methodology that exploits specific characteristics f...
International audienceThis paper presents a new methodology that exploits specific characteristics f...
Hill-climbing constitutes one of the simplest way to produce approximate solutions of a combinatoria...
International audienceSolving efficiently complex problems using metaheuristics, and in particular l...
International audienceSolving efficiently complex problems using metaheuristics, and in particular l...
International audienceIn previous work we have introduced a network-based model that abstracts many ...
International audienceSolving efficiently complex problems using metaheuristics, and in particular l...
International audienceIn previous work we have introduced a network-based model that abstracts many ...
International audienceIn previous work we have introduced a network-based model that abstracts many ...
Les problèmes d'optimisation combinatoire sont généralement NP-difficiles et les méthodes exactes de...
Les problèmes d'optimisation combinatoire sont généralement NP-difficiles et les méthodes exactes de...
Many combinatorial optimization problems are hard to solve and in many cases, exact approaches are i...
Many combinatorial optimization problems are hard to solve and in many cases, exact approaches are i...
The concept of fitness landscape (or adaptive landscape) was introduce par S. Wright in the field of...
International audienceThis paper presents a new methodology that exploits specific characteristics f...
International audienceThis paper presents a new methodology that exploits specific characteristics f...
International audienceThis paper presents a new methodology that exploits specific characteristics f...
Hill-climbing constitutes one of the simplest way to produce approximate solutions of a combinatoria...
International audienceSolving efficiently complex problems using metaheuristics, and in particular l...
International audienceSolving efficiently complex problems using metaheuristics, and in particular l...
International audienceIn previous work we have introduced a network-based model that abstracts many ...
International audienceSolving efficiently complex problems using metaheuristics, and in particular l...
International audienceIn previous work we have introduced a network-based model that abstracts many ...
International audienceIn previous work we have introduced a network-based model that abstracts many ...