Journal ArticleDOI
An Improved Parent-Centric Mutation With Normalized Neighborhoods for Inducing Niching Behavior in Differential Evolution
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TLDR
A niching scheme integrated with DE is suggested for achieving a stable and efficient nICHing behavior by combining the newly proposed parent-centric mutation operator with synchronous crowding replacement rule.Abstract:
In real life, we often need to find multiple optimally sustainable solutions of an optimization problem Evolutionary multimodal optimization algorithms can be very helpful in such cases They detect and maintain multiple optimal solutions during the run by incorporating specialized niching operations in their actual framework Differential evolution (DE) is a powerful evolutionary algorithm (EA) well-known for its ability and efficiency as a single peak global optimizer for continuous spaces This article suggests a niching scheme integrated with DE for achieving a stable and efficient niching behavior by combining the newly proposed parent-centric mutation operator with synchronous crowding replacement rule The proposed approach is designed by considering the difficulties associated with the problem dependent niching parameters (like niche radius) and does not make use of such control parameter The mutation operator helps to maintain the population diversity at an optimum level by using well-defined local neighborhoods Based on a comparative study involving 13 well-known state-of-the-art niching EAs tested on an extensive collection of benchmarks, we observe a consistent statistical superiority enjoyed by our proposed niching algorithmread more
Citations
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Journal ArticleDOI
Recent advances in differential evolution – An updated survey
TL;DR: It is found that it is a high time to provide a critical review of the latest literatures published and also to point out some important future avenues of research on DE.
Journal ArticleDOI
Differential evolution with multi-population based ensemble of mutation strategies
TL;DR: A multi-population based approach is proposed to realize the adapted ensemble of multiple strategies of differential evolution, thereby resulting in a new DE variant named multi- Population ensemble DE (MPEDE) which simultaneously consists of three mutation strategies.
Journal ArticleDOI
Bio-inspired computation: Where we stand and what's next
Javier Del Ser,Javier Del Ser,Eneko Osaba,Daniel Molina,Xin-She Yang,Sancho Salcedo-Sanz,David Camacho,Swagatam Das,Ponnuthurai Nagaratnam Suganthan,Carlos A. Coello Coello,Francisco Herrera +10 more
TL;DR: The main purpose of this paper is to outline the state of the art and to identify open challenges concerning the most relevant areas within bio-inspired optimization, thereby highlighting the need for reaching a consensus and joining forces towards achieving valuable insights into the understanding of this family of optimization techniques.
Journal ArticleDOI
Differential Evolution: A review of more than two decades of research
TL;DR: The journey of Differential Evolution is shown through its basic aspects like population generation, mutation schemes, crossover schemes, variation in parameters and hybridized variants along with various successful applications of DE.
Journal ArticleDOI
Ensemble of differential evolution variants
Guohua Wu,Guohua Wu,Xin Shen,Haifeng Li,Huangke Chen,Anping Lin,Ponnuthurai Nagaratnam Suganthan +6 more
TL;DR: The success of EDEV reveals that, through an appropriate ensemble framework, different DE variants of different merits can support one another to cooperatively solve optimization problems.
References
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Book
Differential Evolution: A Practical Approach to Global Optimization (Natural Computing Series)
TL;DR: This volume explores the differential evolution (DE) algorithm in both principle and practice and is a valuable resource for professionals needing a proven optimizer and for students wanting an evolutionary perspective on global numerical optimization.
Journal ArticleDOI
Differential Evolution: A Survey of the State-of-the-Art
TL;DR: A detailed review of the basic concepts of DE and a survey of its major variants, its application to multiobjective, constrained, large scale, and uncertain optimization problems, and the theoretical studies conducted on DE so far are presented.
Journal ArticleDOI
The Competitive Exclusion Principle
TL;DR: By emphasizing the very aspects that might result in their denial of them were they less plain the authors can keep the principle explicitly present in their minds untit they see if its implications are, or are noty as unpleasant as their subconscious might suppose.
Book ChapterDOI
A Comparative Analysis of Selection Schemes Used in Genetic Algorithms
David E. Goldberg,Kalyanmoy Deb +1 more
TL;DR: A number of selection schemes commonly used in modern genetic algorithms are compared on the basis of solutions to deterministic difference or differential equations, verified through computer simulations to provide convenient approximate or exact solutions and useful convergence time and growth ratio estimates.
Related Papers (5)
Differential Evolution – A Simple and Efficient Heuristic for Global Optimization over Continuous Spaces
Rainer Storn,Kenneth Price +1 more