This book aims at attracting the interest of researchers and practitioners around the applicability of meta-heuristic algorithms to practical scenarios arising from different knowledge disciplines. Emphasis is placed on evolutionary algorithms and swarm intelligence as computational means to efficiently balance the tradeoff between optimality of the produced solutions and the complexity derived from their estimation. In summary, this book serves as a good start point for early-stage investigators in the initial steps of their research on meta-heuristics, grounded on both a thorough literature review and the practical orientation of its contents
Solving complex optimization problems can be painstakingly difficult endeavor considering multiple a...
In recent years, there have been significant advances in the theory and application of meta-heuristi...
There are numerous optimisation problems for which heuristics are currently the only practical solut...
The vast majority of real-world problems can be expressed as an optimisation task by formulating an ...
Conventional and classical optimization methods are not efficient enough to deal with complicated, N...
Metaheuristics, and evolutionary algorithms in particular, are known to provide efficient, adaptable...
Meta-heuristics are practical optimisation-techniques I a pragmatic approach to NP-hard optimisation...
The emergence of different metaheuristics and their new variants in recent years has made the defini...
The emergence of different metaheuristics and their new variants in recent years has made the defini...
Optimization problems appear in many fields, as various as identification problems, supervised learn...
Abstract: Biological systems are, by their very nature, adaptive. However, the meta-heuristic search...
The fields of machine meta-learning and hyper-heuristic optimisation have developed mostly independe...
“… an excellent book if you want to learn about a number of individual metaheuristics." (U. Aickelin...
This timely review volume summarizes the state-of-the-art developments in nature-inspired algorithms...
none3siA specialized thread of metaheuristic research, bordering and often overlapping with Artifici...
Solving complex optimization problems can be painstakingly difficult endeavor considering multiple a...
In recent years, there have been significant advances in the theory and application of meta-heuristi...
There are numerous optimisation problems for which heuristics are currently the only practical solut...
The vast majority of real-world problems can be expressed as an optimisation task by formulating an ...
Conventional and classical optimization methods are not efficient enough to deal with complicated, N...
Metaheuristics, and evolutionary algorithms in particular, are known to provide efficient, adaptable...
Meta-heuristics are practical optimisation-techniques I a pragmatic approach to NP-hard optimisation...
The emergence of different metaheuristics and their new variants in recent years has made the defini...
The emergence of different metaheuristics and their new variants in recent years has made the defini...
Optimization problems appear in many fields, as various as identification problems, supervised learn...
Abstract: Biological systems are, by their very nature, adaptive. However, the meta-heuristic search...
The fields of machine meta-learning and hyper-heuristic optimisation have developed mostly independe...
“… an excellent book if you want to learn about a number of individual metaheuristics." (U. Aickelin...
This timely review volume summarizes the state-of-the-art developments in nature-inspired algorithms...
none3siA specialized thread of metaheuristic research, bordering and often overlapping with Artifici...
Solving complex optimization problems can be painstakingly difficult endeavor considering multiple a...
In recent years, there have been significant advances in the theory and application of meta-heuristi...
There are numerous optimisation problems for which heuristics are currently the only practical solut...