On classifications of fitness functions
Theoretical aspects of evolutionary computing
Tabu Search
On the analysis of the (1+ 1) evolutionary algorithm
Theoretical Computer Science
Artificial Immune Systems: A New Computational Intelligence Paradigm
Artificial Immune Systems: A New Computational Intelligence Paradigm
Contemporary Evolution Strategies
Proceedings of the Third European Conference on Advances in Artificial Life
On the Analysis of Dynamic Restart Strategies for Evolutionary Algorithms
PPSN VII Proceedings of the 7th International Conference on Parallel Problem Solving from Nature
Runtime Analysis of the (μ+1) EA on Simple Pseudo-Boolean Functions
Evolutionary Computation
Theoretical Aspects of Local Search (Monographs in Theoretical Computer Science. An EATCS Series)
Theoretical Aspects of Local Search (Monographs in Theoretical Computer Science. An EATCS Series)
Rigorous Runtime Analysis of Inversely Fitness Proportional Mutation Rates
Proceedings of the 10th international conference on Parallel Problem Solving from Nature: PPSN X
Immunological Computation: Theory and Applications
Immunological Computation: Theory and Applications
On the utility of the population size for inversely fitness proportional mutation rates
Proceedings of the tenth ACM SIGEVO workshop on Foundations of genetic algorithms
Comparison of simple diversity mechanisms on plateau functions
Theoretical Computer Science
Maximal age in randomized search heuristics with aging
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Immune inspired somatic contiguous hypermutation for function optimisation
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartI
IEEE Transactions on Evolutionary Computation
Learning and optimization using the clonal selection principle
IEEE Transactions on Evolutionary Computation
On benefits and drawbacks of aging strategies for randomized search heuristics
Theoretical Computer Science
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Quite different search heuristics make use of the concept of assigning an age to search points and systematically remove search points that are too old from the search process. In evolutionary computation one defines some finite maximal lifespan and assigns age 0 to each new search point. In artificial immune systems static pure aging is used. There a finite maximal lifespan is defined but new search points inherit the age of their origin if they do not excel in function value. Both aging mechanisms are supposed to increase the capabilities of the respective search heuristics. A rigorous analysis for two typical difficult situations sheds light on similarities and differences. Considering the behavior on plateaus of constant function values and in local optima both methods are shown to have their strengths. A third aging operator is introduced that provably shares the advantages of both aging mechanisms.