Thresheld convergence is a technique designed to effectively separate the processes of exploration and exploitation. This paper addresses the design of ...
Abstract—When optimizing multi-modal spaces, effective search techniques must carefully balance two conflicting tasks: exploration and exploitation.
This paper addresses the design of thresheld convergence in the context of evolution strategies by analyzing the behavior of the standard (μ, ...
Thresheld convergence is a technique designed to effectively separate the processes of exploration and exploitation. This paper addresses the design of ...
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In this paper, a global optimum-based search strategy is proposed to alleviate the situation that the differential evolution (DE) usually sticks into a ...
A fitness threshold can be set, and the algorithm can be terminated when an individual achieves a fitness value above the threshold. Convergence criteria ...
A hybrid approach that combines the (1+1)-ES and threshold selection methods is developed. The framework of the new experimentalism is used to perform a ...
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In this paper, an improved ACDE (Adaptive Cauchy Differential Evolution) algorithm with faster convergence speed, called ACDE2, is suggested. The baseline ACDE ...
The goal of thresheld convergence is to improve the performance of search techniques during the first phase of exploration and through the development of ...
Elitism has the most positive impact score of 0.165, while. Threshold convergence is the most negative at −0.398. Other modules such as Pairwise Selection seem ...