We introduce the Spacing Memetic Algorithm (SMA), a formal evolutionary model devoted to a systematic control of spacing (distances) among individuals. SMA uses search space dista...
Daniel Cosmin Porumbel, Jin-Kao Hao, Pascale Kuntz
Premature convergence is a major problem of Particle Swarm Optimization (PSO).Although many strategies have been proposed, there is still some work needed to do in high-dimensional...
It has previously been shown analytically and experimentally that continuous Estimation of Distribution Algorithms (EDAs) based on the normal pdf can easily suffer from premature ...
Niching schemes, which sustain population diversity and let an evolutionary population avoid premature convergence, have been extensively studied in the research field of evoluti...
The fundamental dichotomy in evolutionary algorithms is that between exploration and exploitation. Recently, several algorithms [8, 9, 14, 16, 17, 20] have been introduced that gu...
This paper presents a modification of the particle swarm optimization algorithm (PSO) intended to combat the problem of premature convergence observed in many applications of PSO. ...
The capability of multi-objective evolutionary algorithms (MOEAs) to handle premature convergence is critically important when applied to real-world problems. Their highly multi-mo...
Jianjun Hu, Kisung Seo, Zhun Fan, Ronald C. Rosenb...
The goal of an Evolutionary Algorithm(EA) is to find the optimal solution to a given problem by evolving a set of initial potential solutions. When the problem is multi-modal, an ...
Konstantinos Bousmalis, Gillian M. Hayes, Jeffrey ...
In continuous black-box optimization, various stochastic local search techniques are often employed, with various remedies for fighting the premature convergence. This paper surve...