Everything about Mutation (evolutionary algorithm)

🧭 Start here: a 6-step reading path

1. Read the overview: Mutation (evolutionary algorithm)A 5-minute orientation
2. Skim a recent paper: Quantum differential evolutionary algorithm with quantum-adaptive mutation strategy and population state evaluation framework for high-dimensional problemsInfluential work since 2022
3. Pick up a classic book: Genetic ProgrammingThe most-reprinted book on the subject
4. Read the landmark paper: An Evolutionary Algorithm With Guided Mutation for the Maximum Clique ProblemCited 188 times
5. Go sideways: Crossover (evolutionary algorithm)A closely related topic
6. Go sideways: Chromosome (evolutionary algorithm)A closely related topic

🏆 Landmark papers (most cited)

• An Evolutionary Algorithm With Guided Mutation for the Maximum Clique Problem

  Q. Zhang, J. Sun, E. Tsang · 2005 · IEEE Transactions on Evolutionary Computation · 188 citations

• An adaptive differential evolutionary algorithm incorporating multiple mutation strategies for the economic load dispatch problem

  Qiang Zhang, Dexuan Zou, Na Duan · 2019 · Applied Soft Computing · 72 citations

• The ( $$1+\lambda $$ 1 + λ ) Evolutionary Algorithm with Self-Adjusting Mutation Rate

  Benjamin Doerr, Christian Gießen, Carsten Witt · 2018 · Algorithmica · 53 citations

• QoS-aware Big service composition using MapReduce based evolutionary algorithm with guided mutation

  Chandrashekar Jatoth, G.R. Gangadharan, Ugo Fiore · 2018 · Future Generation Computer Systems · 53 citations

• Bearing defect identification via evolutionary algorithm with adaptive wavelet mutation strategy

  Sumika Chauhan, Manmohan Singh, Ashwani Kumar Aggarwal · 2021 · Measurement · 44 citations

• An adaptive evolutionary algorithm with intelligent mutation local searchers for designing multidrug therapies for HIV

  Ferrante Neri, Jari Toivanen, Raino A. E. Mäkinen · 2007 · Applied Intelligence · 44 citations

• Grain boundary structure search by using an evolutionary algorithm with effective mutation methods

  Chaoming Yang, Mingfei Zhang, Liang Qi · 2020 · Computational Materials Science · 26 citations

• Multiobjective evolutionary algorithm with a discrete differential mutation operator developed for service restoration in distribution systems

  Danilo Sipoli Sanches, João Bosco A. London, Alexandre Cláudio B. Delbem · 2014 · International Journal of Electrical Power & Energy Systems · 26 citations

🆕 Influential since 2022

• Quantum differential evolutionary algorithm with quantum-adaptive mutation strategy and population state evaluation framework for high-dimensional problems

  Wu Deng, Jiarui Wang, Aibin Guo · 2024 · Information Sciences · 48 citations

• A Dual Mutation-Based Evolutionary Algorithm for Dynamic Multiobjective Optimization With Undetectable Changes

  Yuanchao Liu, Lixin Tang, Jinliang Ding · 2025 · IEEE Transactions on Evolutionary Computation · 20 citations

• Multi-algorithm based evolutionary strategy with Adaptive Mutation Mechanism for Constraint Engineering Design Problems

  Rohit Salgotra, Sayedali Mirjalili · 2024 · Expert Systems with Applications · 18 citations

• Fuzzy logic applied to tunning mutation size in evolutionary algorithms

  Krzysztof Pytel · 2025 · Scientific Reports · 10 citations

• Enhancing Solid Oxide Fuel Cell Efficiency Through Advanced Model Identification Using Differential Evolutionary Mutation Fennec Fox Algorithm

  Manish Kumar Singla, Jyoti Gupta, Ramesh Kumar · 2025 · International Journal of Computational Intelligence Systems · 7 citations

📚 Books worth reading

• Genetic ProgrammingKrzysztof Krawiec · 2013
• Intelligent Information and Database SystemsAli Selamat · 2013
• Evolutionary Computation, Machine Learning and Data Mining in BioinformaticsLeonardo Vanneschi · 2012
• Self-adaptive heuristics for evolutionary computationOliver Kramer · 2008
• Principles of gene manipulation and genomicsS. B. Primrose · 2006
• Stable Mutations for Evolutionary AlgorithmsAndrzej Obuchowicz · 2018
• Knowledge Incorporation in Evolutionary ComputationYaochu Jin · 2005
• Evolutionary algorithmsWilliam M. Spears · 2000

Ranked by number of editions on Open Library, a rough measure of how lasting a book is.

🔗 Related topics

• Crossover (evolutionary algorithm) Crossover in evolutionary algorithms and evolutionary computation, also called recombination, is a genetic operator used to combine the genetic information…
• Chromosome (evolutionary algorithm) A chromosome or genotype in evolutionary algorithms (EA) is a set of parameters which define a proposed solution of the problem that the evolutionary algorithm…
• Genetic operator A genetic operator is an operator used in evolutionary algorithms (EA) to guide the algorithm towards a solution to a given problem. There are three main…
• Evolutionary algorithm Evolutionary algorithms (EA) reproduce essential elements of biological evolution in a computer algorithm in order to solve "difficult" problems, at least…
• Genotypic and phenotypic repair Genotypic and phenotypic repair are optional components of an evolutionary algorithm (EA). An EA reproduces essential elements of biological evolution…
• Evolutionary computation Evolutionary computation (EC) from computer science is a family of algorithms for global optimization inspired by biological evolution, and a subfield…
• Genetic algorithm A genetic algorithm (GA) is a metaheuristic inspired by the process of natural selection that belongs to the larger class of evolutionary algorithms (EA)…
• Premature convergence Premature convergence is an unwanted effect in evolutionary algorithms (EA), a metaheuristic that mimics the basic principles of biological evolution as…