Abstract
In this paper we consider the upper and lower bounds on probability to generate the solutions of sufficient quality using evolutionary strategies of two kinds: the (1+1)-ES and the (1,λ)-ES (see e.g. [1,2]). The results are obtained in terms of monotone bounds [3] on transition probabilities of the mutation operator. Particular attention is given to the computational complexity of mutation procedure for the NP-hard combinatorial optimization problems.
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References
Bäck, T., Schwefel H.-P.: An overview of evolutionary algorithms for parameter optimization, Evolutionary Computation, 1(1) (1993) 1–23
Rechenberg I.: Evolutionsstrategie’94. Formann-Holzboog Verlag, Stuttgart (1994)
Eremeev A.V.: Modeling and Analysis of Genetic Algorithm with Tournament Selection. Proc. of Artificial Evolution Conference (AE’99). Lecture Notes in Computer Science, Vol. 1829. Springer Verlag (2000) 84–95
Motwani, R. and Raghavan, P.: Randomized Algorithms. Cambridge University Press (1995)
Rudolph, G.: Finite Markov Chain Results in Evolutionary Computation: A Tour d’Horizon, Fundamenta Informaticae 35(1-4) (1998) 67–89
Arora, S., Lund, C.: Hardness of approximations. Approximation Algorithms for NP-Hard Problems. Ed. by S.D. Hochbaum. PWS Publishing Company, (1995) 399–446
Garey, M.R. and Johnson, D.S.: Computers and intractability. A guide to the theory of NP-completeness. W.H. Freeman and Company, San Francisco (1979)
Ausiello, G., Protasi, M.: Local search, reducibility and approximability of NP-optimization problems. Information Processing Letters, 54 (1995) 73–79
Ko, K.: Some observations on the probabilistic algorithms and NP-hard problems, Information Processing Letters, 14 (1982) 39–43
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Borisovsky, P.A., Eremeev, A.V. (2001). On Performance Estimates for Two Evolutionary Algorithms. In: Boers, E.J.W. (eds) Applications of Evolutionary Computing. EvoWorkshops 2001. Lecture Notes in Computer Science, vol 2037. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45365-2_17
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DOI: https://doi.org/10.1007/3-540-45365-2_17
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