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  • 1
    Electronic Resource
    Electronic Resource
    Springer
    Algorithmica 26 (2000), S. 290-309 
    ISSN: 1432-0541
    Keywords: Key words. Common intervals of permutations, Genetic algorithm, Linear time algorithm, Random permutations, Monge property, Subtour exchange crossover.
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Mathematics
    Notes: Abstract. Given two permutations of n elements, a pair of intervals of these permutations consisting of the same set of elements is called a common interval . Some genetic algorithms based on such common intervals have been proposed for sequencing problems and have exhibited good prospects. In this paper we propose three types of fast algorithms to enumerate all common intervals: (i) a simple O(n 2 ) time algorithm (LHP), whose expected running time becomes O(n) for two randomly generated permutations, (ii) a practically fast O(n 2 ) time algorithm (MNG) using the reverse Monge property, and (iii) an O(n+K) time algorithm (RC), where K $(\leq {n \choose 2})$ is the number of common intervals. It will also be shown that the expected number of common intervals for two random permutations is O(1) . This result gives a reason for the phenomenon that the expected time complexity O(n) of the algorithm LHP is independent of K . Among the proposed algorithms, RC is most desirable from the theoretical point of view; however, it is quite complicated compared with LHP and MNG. Therefore, it is possible that RC is slower than the other two algorithms in some cases. For this reason, computational experiments for various types of problems with up to n=10 6 are conducted. The results indicate that (i) LHP and MNG are much faster than RC for two randomly generated permutations, and (ii) MNG is rather slower than LHP for random inputs; however, there are cases in which LHP requires Ω(n 2 ) time, but MNG runs in o(n 2 ) time and is faster than both LHP and RC.
    Type of Medium: Electronic Resource
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  • 2
    Electronic Resource
    Electronic Resource
    Springer
    Journal of combinatorial optimization 3 (1999), S. 95-114 
    ISSN: 1573-2886
    Keywords: MAX SAT ; SAT ; local search ; neighborhood
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract For problems SAT and MAX SAT, local search algorithms are widely acknowledged as one of the most effective approaches. Most of the local search algorithms are based on the 1-flip neighborhood, which is the set of solutions obtainable by flipping the truth assignment of one variable. In this paper, we consider r-flip neighborhoods for r ≥ 2, and propose, for r = 2, 3, new implementations that reduce the number of candidates in the neighborhood without sacrificing the solution quality. For 2-flip (resp., 3-flip) neighborhood, we show that its expected size is O(n + m) (resp., O(m + t2n)), which is usually much smaller than the original size O(n2) (resp., O(n3)), where n is the number of variables, m is the number of clauses and t is the maximum number of appearances of one variable. Computational results tell that these estimates by the expectation well represent the real performance.
    Type of Medium: Electronic Resource
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