On benefits and drawbacks of aging strategies for randomized search heuristics

DOI10.1016/j.tcs.2010.03.032zbMath1208.68201OpenAlexW2017801775MaRDI QIDQ627105

Thomas Jansen, Christine Zarges

Publication date: 21 February 2011

Published in: Theoretical Computer Science (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.tcs.2010.03.032

zbMATH Keywords

evolutionary algorithmsagingruntime analysisartificial immune systems

Mathematics Subject Classification ID

Searching and sorting (68P10) Learning and adaptive systems in artificial intelligence (68T05) Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.) (68T20) Probability in computer science (algorithm analysis, random structures, phase transitions, etc.) (68Q87)

Related Items (3)

A tight runtime analysis for the \((\mu + \lambda)\) EA ⋮ Analyzing randomized search heuristics via stochastic domination ⋮ Lower bounds on the runtime of crossover-based algorithms via decoupling and family graphs

Uses Software

• Tabu search

Cites Work

• Theoretical aspects of local search.
• Comparison of simple diversity mechanisms on plateau functions
• On the analysis of the \((1+1)\) evolutionary algorithm
• Cooperative mutation based evolutionary programming for continuous function optimization
• Advances in artificial life. Third European conference on artificial life, Granada, Spain, June 4-6, 1995. Proceedings
• An immune algorithm with stochastic aging and Kullback entropy for the chromatic number problem
• On the utility of the population size for inversely fitness proportional mutation rates
• Evolutionary Computation in Combinatorial Optimization
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item

This page was built for publication: On benefits and drawbacks of aging strategies for randomized search heuristics