Optimization problems appear in many fields, as various as identification problems, supervised learning of neural networks, shortest path problems, etc. Metaheuristics [22] are a family of optimization algorithms, often applied to "hard " combinatorial problems for which no more efficient method is known. They have the advantage of being generi
This paper presents a quick review of the basic concepts and essential steps for implementing of met...
In this paper, a new branch of computational intelligence named estimation-based metaheuristic is in...
Metaheuristics are the most exciting development in approximate optimization techniques of the last ...
The majority of the algorithms used to solve hard optimization problems today are population metaheu...
International audienceThis chapter describes metaheuristics evolving a set of solutions and generati...
This book aims at attracting the interest of researchers and practitioners around the applicability ...
International audienceDuring the past few years, research in applying machine learning (ML) to desig...
none2In many real life settings, high quality solutions to hard optimization problems such as flight...
Many problems in data mining and machine learning are related to optimization, and optimization tech...
“… an excellent book if you want to learn about a number of individual metaheuristics." (U. Aickelin...
A specialized thread of metaheuristic research, bordering and often overlapping with Artificial Inte...
Metaheuristics are general algorithmic frameworks, often nature-inspired, designed to solve complex ...
When facing complex and unknown problems, it is very natural to use rules of thumb, common sense, tr...
Swarm intelligence has becoming a powerful technique in solving design and scheduling tasks. Metaheu...
In recent years, there have been significant advances in the theory and application of metaheuristic...
This paper presents a quick review of the basic concepts and essential steps for implementing of met...
In this paper, a new branch of computational intelligence named estimation-based metaheuristic is in...
Metaheuristics are the most exciting development in approximate optimization techniques of the last ...
The majority of the algorithms used to solve hard optimization problems today are population metaheu...
International audienceThis chapter describes metaheuristics evolving a set of solutions and generati...
This book aims at attracting the interest of researchers and practitioners around the applicability ...
International audienceDuring the past few years, research in applying machine learning (ML) to desig...
none2In many real life settings, high quality solutions to hard optimization problems such as flight...
Many problems in data mining and machine learning are related to optimization, and optimization tech...
“… an excellent book if you want to learn about a number of individual metaheuristics." (U. Aickelin...
A specialized thread of metaheuristic research, bordering and often overlapping with Artificial Inte...
Metaheuristics are general algorithmic frameworks, often nature-inspired, designed to solve complex ...
When facing complex and unknown problems, it is very natural to use rules of thumb, common sense, tr...
Swarm intelligence has becoming a powerful technique in solving design and scheduling tasks. Metaheu...
In recent years, there have been significant advances in the theory and application of metaheuristic...
This paper presents a quick review of the basic concepts and essential steps for implementing of met...
In this paper, a new branch of computational intelligence named estimation-based metaheuristic is in...
Metaheuristics are the most exciting development in approximate optimization techniques of the last ...