Add to ORKGAbstract — Due to the stochastic nature, there are several concerns on the effectiveness and robustness of evolutionary algorithms when applied to solve different kinds of optimization problems in power systems field. To address this issue, this paper provides a comparative analysis of several evolutionary algorithms based on parametric and non-parametric statistical tests. Numerical examples are based on hydrothermal system operation and transmission pricing optimization problems
The modern heuristic techniques mainly include the application of the artificial intelligence approa...
It has become more evident that in complex problems the performance of a genetic algorithm depends o...
In the present paper, Evolutionary Algorithms (EAs) computing techniques have been used for economic...
Due to the stochastic nature, there are several concerns on the effectiveness and robustness of evol...
The scope of optimization in power system is ample. In general, optimization helps efficient and eco...
This book compares the performance of various evolutionary computation (EC) techniques when they are...
This paper gives an overview of some stochastic optimization strategies, namely, evolution strategie...
This paper presents a new statistics-based evolutionary algorithm to improve the qualities of power ...
This paper theoretically compares the performance of simulated annealing and evolutionary algorithms...
Evolutionary algorithms (EAs) have emerged as an efficient alternative to deal with real-world appli...
In real-world optimization problems, even though the solution quality is of great importance, the ro...
This paper proposes a new evolutionary algorithm namely Evolutionary Mating Algorithm (EMA) to solve...
The economic operation problem in electric power systems involves the scheduling of both thermal and...
Despite the continuous advancement of Evolutionary Algorithms (EAs) and their numerous successful ap...
D.Ing. (Electrical Engineering)Abstract: Evolutionary Algorithms (EAs) refer to a group of optimizat...
The modern heuristic techniques mainly include the application of the artificial intelligence approa...
It has become more evident that in complex problems the performance of a genetic algorithm depends o...
In the present paper, Evolutionary Algorithms (EAs) computing techniques have been used for economic...
Due to the stochastic nature, there are several concerns on the effectiveness and robustness of evol...
The scope of optimization in power system is ample. In general, optimization helps efficient and eco...
This book compares the performance of various evolutionary computation (EC) techniques when they are...
This paper gives an overview of some stochastic optimization strategies, namely, evolution strategie...
This paper presents a new statistics-based evolutionary algorithm to improve the qualities of power ...
This paper theoretically compares the performance of simulated annealing and evolutionary algorithms...
Evolutionary algorithms (EAs) have emerged as an efficient alternative to deal with real-world appli...
In real-world optimization problems, even though the solution quality is of great importance, the ro...
This paper proposes a new evolutionary algorithm namely Evolutionary Mating Algorithm (EMA) to solve...
The economic operation problem in electric power systems involves the scheduling of both thermal and...
Despite the continuous advancement of Evolutionary Algorithms (EAs) and their numerous successful ap...
D.Ing. (Electrical Engineering)Abstract: Evolutionary Algorithms (EAs) refer to a group of optimizat...
The modern heuristic techniques mainly include the application of the artificial intelligence approa...
It has become more evident that in complex problems the performance of a genetic algorithm depends o...
In the present paper, Evolutionary Algorithms (EAs) computing techniques have been used for economic...