Journal ArticleDOI
Exploration and exploitation in evolutionary algorithms: A survey
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TLDR
A fresh treatment is introduced that classifies and discusses existing work within three rational aspects: what and how EA components contribute to exploration and exploitation; when and how Exploration and exploitation are controlled; and how balance between exploration and exploited is achieved.Abstract:
“Exploration and exploitation are the two cornerstones of problem solving by search.” For more than a decade, Eiben and Schippers' advocacy for balancing between these two antagonistic cornerstones still greatly influences the research directions of evolutionary algorithms (EAs) [1998]. This article revisits nearly 100 existing works and surveys how such works have answered the advocacy. The article introduces a fresh treatment that classifies and discusses existing work within three rational aspects: (1) what and how EA components contribute to exploration and exploitation; (2) when and how exploration and exploitation are controlled; and (3) how balance between exploration and exploitation is achieved. With a more comprehensive and systematic understanding of exploration and exploitation, more research in this direction may be motivated and refined.read more
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Journal ArticleDOI
SCA: A Sine Cosine Algorithm for solving optimization problems
TL;DR: The SCA algorithm obtains a smooth shape for the airfoil with a very low drag, which demonstrates that this algorithm can highly be effective in solving real problems with constrained and unknown search spaces.
Journal ArticleDOI
Equilibrium optimizer: A novel optimization algorithm
TL;DR: A well-defined “generation rate” term is proved to invigorate EO’s ability in exploration, exploitation, and local minima avoidance, and its performance is statistically similar to SHADE and LSHADE-SPACMA.
A Exploration and Exploitation in Evolutionary Algorithms: A Survey
TL;DR: In this paper, a good ratio between exploration and exploitation of a search space is defined as the ratio between the probability that a search algorithm is successful and the probability of being successful.
Journal ArticleDOI
Many-Objective Evolutionary Algorithms: A Survey
TL;DR: A survey of MaOEAs is reported and seven classes of many-objective evolutionary algorithms proposed are categorized into seven classes: relaxed dominance based, diversity-based, aggregation- based, indicator-Based, reference set based, preference-based and dimensionality reduction approaches.
Journal ArticleDOI
Optimizing connection weights in neural networks using the whale optimization algorithm
TL;DR: The qualitative and quantitative results prove that the proposed WOA-based trainer is able to outperform the current algorithms on the majority of datasets in terms of both local optima avoidance and convergence speed.
References
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Book
Genetic algorithms in search, optimization, and machine learning
TL;DR: In this article, the authors present the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields, including computer programming and mathematics.
Book
Adaptation in natural and artificial systems
TL;DR: Names of founding work in the area of Adaptation and modiication, which aims to mimic biological optimization, and some (Non-GA) branches of AI.
Journal ArticleDOI
Differential Evolution – A Simple and Efficient Heuristic for Global Optimization over Continuous Spaces
Rainer Storn,Kenneth Price +1 more
TL;DR: In this article, a new heuristic approach for minimizing possibly nonlinear and non-differentiable continuous space functions is presented, which requires few control variables, is robust, easy to use, and lends itself very well to parallel computation.
Book
Genetic Programming: On the Programming of Computers by Means of Natural Selection
TL;DR: This book discusses the evolution of architecture, primitive functions, terminals, sufficiency, and closure, and the role of representation and the lens effect in genetic programming.
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Differential Evolution – A Simple and Efficient Heuristic for Global Optimization over Continuous Spaces
Rainer Storn,Kenneth Price +1 more