The book addresses some of the most recent issues, with the theoretical and methodological aspects, of evolutionary multi-objective optimization problems and the various design challenges using different hybrid intelligent approaches. Multi-objective optimization has been available for about two decades, and its application in real-world problems is continuously increasing. Furthermore, many applications function more effectively using a hybrid systems approach. The book presents hybrid techniques based on Artificial Neural Network, Fuzzy Sets, Automata Theory, other metaheuristic or classical algorithms, etc. The book examines various examples of algorithms in different real-world application domains as graph growing problem, speech synthe...
The book provides readers with a snapshot of the state of the art in the field of nature-inspired co...
In this paper we discuss three topics that are present in the area of real-world optimization, but a...
Genetic algorithms are group optimisation techniques which can handle multiple objective functions s...
Genetic Algorithms (GAs) are one of several techniques in the family of Evolutionary Algorithms - al...
This book describes recent advances on hybrid intelligent systems using soft computing techniques fo...
Evolutionary algorithms are bio-inspired algorithms based on Darwin’s theory of evolution. They are ...
Genetic algorithms are extremely popular methods for solving optimization problems. They are a popul...
Abstract: Various issues of the design and application of multiobjective evolutionary algorithms to ...
Since the introduction of genetic algorithms in the 1970s, an enormous number of articles together w...
Creating or preparing Multi-objective formulations are a realistic models for many complex engineeri...
Evolutionary algorithms and metaheuristics are widely used to provide efficient and effective approx...
Evolutionary processes have attracted considerable interest in recent years for solving a variety of...
In this thesis, the basic principles and concepts of single and multi-objective Genetic Algorithms (...
Use of non-deterministic algorithms for solving multi-variable optimization problems is widely used ...
This paper provides a review on current developments in genetic algorithms. The discussion includes ...
The book provides readers with a snapshot of the state of the art in the field of nature-inspired co...
In this paper we discuss three topics that are present in the area of real-world optimization, but a...
Genetic algorithms are group optimisation techniques which can handle multiple objective functions s...
Genetic Algorithms (GAs) are one of several techniques in the family of Evolutionary Algorithms - al...
This book describes recent advances on hybrid intelligent systems using soft computing techniques fo...
Evolutionary algorithms are bio-inspired algorithms based on Darwin’s theory of evolution. They are ...
Genetic algorithms are extremely popular methods for solving optimization problems. They are a popul...
Abstract: Various issues of the design and application of multiobjective evolutionary algorithms to ...
Since the introduction of genetic algorithms in the 1970s, an enormous number of articles together w...
Creating or preparing Multi-objective formulations are a realistic models for many complex engineeri...
Evolutionary algorithms and metaheuristics are widely used to provide efficient and effective approx...
Evolutionary processes have attracted considerable interest in recent years for solving a variety of...
In this thesis, the basic principles and concepts of single and multi-objective Genetic Algorithms (...
Use of non-deterministic algorithms for solving multi-variable optimization problems is widely used ...
This paper provides a review on current developments in genetic algorithms. The discussion includes ...
The book provides readers with a snapshot of the state of the art in the field of nature-inspired co...
In this paper we discuss three topics that are present in the area of real-world optimization, but a...
Genetic algorithms are group optimisation techniques which can handle multiple objective functions s...