Drift analysis and average time complexity of evolutionary algorithms
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چکیده
منابع مشابه
Drift analysis and average time complexity of evolutionary algorithms
The computational time complexity is an important topic in the theory of evolutionary algorithms (EAs). This paper reports some new results on the average time complexity of EAs. Based on drift analysis, some useful drift conditions for deriving the time complexity of EAs are studied, including conditions under which an EA will take no more than polynomial time (in problem size) to solve a prob...
متن کاملErratum to: Drift analysis and average time complexity of evolutionary algorithms [Artificial Intelligence 127 (2001) 57-85]
The proof of Theorem 6 in the paper by J. He and X. Yao [Artificial Intelligence 127 (1) (2001) 57–85] contains a mistake, although the theorem is correct [S. Droste et al., Theoret. Comput. Sci. 276 (2002) 51–81]. This note gives a revised proof and theorem. It turns out that the revised theorem is more general than the original one given an evolutionary algorithm with mutation probability pm ...
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One of the easiest randomized greedy optimization algorithms is the following evolutionary algorithm which aims at maximizing a boolean function f : {0, 1}n → R. The algorithm starts with a random search point ξ ∈ {0, 1}n, and in each round it flips each bit of ξ with probability c/n independently at random, where c > 0 is a fixed constant. The thus created offspring ξ replaces ξ if and only if...
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Average complexity of Moore's and Hopcroft's algorithms
In this paper we prove that for the uniform distribution on complete deterministic automata, the average time complexity of Moore’s state minimization algorithm is O(n log logn), where n is the number of states in the input automata and the number of letters in the alphabet is fixed. Then, an unusual family of implementations of Hopcroft’s algorithm is characterized, for which the algorithm wil...
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ژورنال
عنوان ژورنال: Artificial Intelligence
سال: 2001
ISSN: 0004-3702
DOI: 10.1016/s0004-3702(01)00058-3