Add to ORKGDue 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
This paper presents a new statistics-based evolutionary algorithm to improve the qualities of power ...
This paper proposes a new evolutionary algorithm namely Evolutionary Mating Algorithm (EMA) to solve...
Many optimization problems admit a number of local optima, among which there is the global optimum. ...
Abstract — Due to the stochastic nature, there are several concerns on the effectiveness and robustn...
The scope of optimization in power system is ample. In general, optimization helps efficient and eco...
Stochastic optimization algorithms are usually evaluated based on performance on high dimensional be...
Nowadays heuristic methods are one of the most used tools for the optimization of problems. The proo...
Despite the continuous advancement of Evolutionary Algorithms (EAs) and their numerous successful ap...
In this study, the best settings of five heuristics are determined for solving a mixed-integer non-l...
The modern heuristic techniques mainly include the application of the artificial intelligence approa...
Evolutionary algorithms (EAs) have emerged as an efficient alternative to deal with real-world appli...
The potential and effectiveness of the newly developed Pareto-based multiobjective evolutionary algo...
Many real world problems in science and engineering can be treated as optimization problems with mul...
In real-world optimization problems, even though the solution quality is of great importance, the ro...
A comparative study of newly developed Pareto-based multiobjective evolutionary algorithms (MOEA) ap...
This paper presents a new statistics-based evolutionary algorithm to improve the qualities of power ...
This paper proposes a new evolutionary algorithm namely Evolutionary Mating Algorithm (EMA) to solve...
Many optimization problems admit a number of local optima, among which there is the global optimum. ...
Abstract — Due to the stochastic nature, there are several concerns on the effectiveness and robustn...
The scope of optimization in power system is ample. In general, optimization helps efficient and eco...
Stochastic optimization algorithms are usually evaluated based on performance on high dimensional be...
Nowadays heuristic methods are one of the most used tools for the optimization of problems. The proo...
Despite the continuous advancement of Evolutionary Algorithms (EAs) and their numerous successful ap...
In this study, the best settings of five heuristics are determined for solving a mixed-integer non-l...
The modern heuristic techniques mainly include the application of the artificial intelligence approa...
Evolutionary algorithms (EAs) have emerged as an efficient alternative to deal with real-world appli...
The potential and effectiveness of the newly developed Pareto-based multiobjective evolutionary algo...
Many real world problems in science and engineering can be treated as optimization problems with mul...
In real-world optimization problems, even though the solution quality is of great importance, the ro...
A comparative study of newly developed Pareto-based multiobjective evolutionary algorithms (MOEA) ap...
This paper presents a new statistics-based evolutionary algorithm to improve the qualities of power ...
This paper proposes a new evolutionary algorithm namely Evolutionary Mating Algorithm (EMA) to solve...
Many optimization problems admit a number of local optima, among which there is the global optimum. ...