Abstract. Hybridizing metaheuristic approaches becomes a common way to improve the efficiency of optimization methods. Many hybridiza-tions deal with the combination of several optimization methods. In this paper we are interested in another type of hybridization, where datamin-ing approaches are combined within an optimization process. Hence, we propose to study the interest of combining metaheuristics and datamin-ing through a short survey that enumerates the different opportunities of such combinations based on literature examples.
In this paper we explore the application of powerful optimisers known as metaheuristic algorithms to...
Combinatorial optimization attracted many researchers since more than three decades. Plenty of clas...
Combinatorial optimization attracted many researchers since more than three decades. Plenty of clas...
International audienceHybridizing metaheuristic approaches becomes a common way to improve the effic...
Abstract The combination of components from different algorithms is currently one of the most succes...
International audienceOver the last two decades, interest on hybrid metaheuristics has risen conside...
The combination of components from different algorithms is currently one of the most successful tren...
The combination of components from different algorithms is currently one of most successful trends i...
International audienceDuring the past few years, research in applying machine learning (ML) to desig...
The hybridization with other techniques for optimization has been one of the most interesting recent...
[EN]This book explains the most prominent and some promising new, general techniques that combine me...
This paper studies with the design of hybrid metaheuristics and their implementations. Hybrid metah...
none2In many real life settings, high quality solutions to hard optimization problems such as flight...
Research in metaheuristics for combinatorial optimization problems has lately experienced a notewort...
Over the last decades, so-called hybrid optimization approaches have become increasingly popular for...
In this paper we explore the application of powerful optimisers known as metaheuristic algorithms to...
Combinatorial optimization attracted many researchers since more than three decades. Plenty of clas...
Combinatorial optimization attracted many researchers since more than three decades. Plenty of clas...
International audienceHybridizing metaheuristic approaches becomes a common way to improve the effic...
Abstract The combination of components from different algorithms is currently one of the most succes...
International audienceOver the last two decades, interest on hybrid metaheuristics has risen conside...
The combination of components from different algorithms is currently one of the most successful tren...
The combination of components from different algorithms is currently one of most successful trends i...
International audienceDuring the past few years, research in applying machine learning (ML) to desig...
The hybridization with other techniques for optimization has been one of the most interesting recent...
[EN]This book explains the most prominent and some promising new, general techniques that combine me...
This paper studies with the design of hybrid metaheuristics and their implementations. Hybrid metah...
none2In many real life settings, high quality solutions to hard optimization problems such as flight...
Research in metaheuristics for combinatorial optimization problems has lately experienced a notewort...
Over the last decades, so-called hybrid optimization approaches have become increasingly popular for...
In this paper we explore the application of powerful optimisers known as metaheuristic algorithms to...
Combinatorial optimization attracted many researchers since more than three decades. Plenty of clas...
Combinatorial optimization attracted many researchers since more than three decades. Plenty of clas...