In the present paper some metrics for evaluating the performance of evolutionary algorithms are considered. The capabilities of two different optimisation approaches are compared on three test cases, represented by the optimisation of orbital transfer trajectories. The complexity of the problem of ranking stochastic algorithms by means of quantitative indices is analyzed by means of a large sample of runs, so as to derive statistical properties of the indices in order to evaluate their usefulness in understanding the actual algorithm capabilities and their possible intrinsic limitations in providing reliable information
Although some convergence proofs of evolutionary and other optimisation algorithms exist, most glo...
This paper proposes a statistical methodology for comparing the performance of stochastic optimizati...
Evolutionary algorithms (EAs) have emerged as an efficient alternative to deal with real-world appli...
In the present paper some metrics for evaluating the performance of evolutionary algorithms are cons...
In the present paper some metrics for evaluating the performance of evolutionary algorithms are cons...
Orbit transfer maneuvers are here considered as benchmark cases for comparing performance of differe...
Orbit transfer maneuvers are here considered as benchmark cases for comparing performance of differe...
In this paper we discuss the procedures to test a global search algorithm applied to a space traject...
Despite the continuous advancement of Evolutionary Algorithms (EAs) and their numerous successful ap...
Reporting the results of optimization algorithms in evolutionary computation is a challenging task w...
Evolutionary algorithms (EA) are a computation tool that utilizes biological principles found in th...
One particular kind of evolutionary algorithms known as Estimation of Distribution Algorithms (EDAs)...
This paper proposes the notion that the experimental results and performance analyses of newly deve...
This paper proposes a statistical methodology for comparing the performance of evolutionary computat...
Optimization with stochastic algorithms has become a relevant approach, specially, in problems with...
Although some convergence proofs of evolutionary and other optimisation algorithms exist, most glo...
This paper proposes a statistical methodology for comparing the performance of stochastic optimizati...
Evolutionary algorithms (EAs) have emerged as an efficient alternative to deal with real-world appli...
In the present paper some metrics for evaluating the performance of evolutionary algorithms are cons...
In the present paper some metrics for evaluating the performance of evolutionary algorithms are cons...
Orbit transfer maneuvers are here considered as benchmark cases for comparing performance of differe...
Orbit transfer maneuvers are here considered as benchmark cases for comparing performance of differe...
In this paper we discuss the procedures to test a global search algorithm applied to a space traject...
Despite the continuous advancement of Evolutionary Algorithms (EAs) and their numerous successful ap...
Reporting the results of optimization algorithms in evolutionary computation is a challenging task w...
Evolutionary algorithms (EA) are a computation tool that utilizes biological principles found in th...
One particular kind of evolutionary algorithms known as Estimation of Distribution Algorithms (EDAs)...
This paper proposes the notion that the experimental results and performance analyses of newly deve...
This paper proposes a statistical methodology for comparing the performance of evolutionary computat...
Optimization with stochastic algorithms has become a relevant approach, specially, in problems with...
Although some convergence proofs of evolutionary and other optimisation algorithms exist, most glo...
This paper proposes a statistical methodology for comparing the performance of stochastic optimizati...
Evolutionary algorithms (EAs) have emerged as an efficient alternative to deal with real-world appli...