Monte Carlo and quasi-Monte Carlo methods in scientific computing: proceedings of a conference at the University of Nevada, Las Vegas, Nevada, USA, June 23-25, 1994
Scientists and engineers are increasingly making use of simulation methods to solve problems which are insoluble by analytical techniques. Monte Carlo methods which make use of probabilistic simulations are frequently used in areas such as numerical integration, complex scheduling, queueing networks, and large-dimensional simulations. This collection of papers arises from a conference held at the University of Nevada, Las Vegas, in 1994. The conference brought together researchers across a range of disciplines whose interests include the theory and application of these methods. This volume provides a timely survey of this field and the new directions in which the field is moving.
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KENJI NAGASAKA and ICHIRO YASUNAGA MonteCarlo Simulations in Genetic Algorithm
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algorithm ANOVA effects application approximation asymptotically binary tree calculations collision Comp congruential pseudorandom numbers constb construction defined Diffusion Monte Carlo dimension dimensional discrepancy DQMC drandid Eichenauer Eichenauer-Herrmann equation error bound coefficients estimate example exponential sums finite field function GF(p GFSR grid Halton sequence implementation integrand inversive congruential inversive congruential pseudorandom L'Ecuyer lattice structure Lemma linear congruential linear congruential method low-discrepancy Math Mathematics matrix method Mersenne prime Ml Ml Model Problem modulus Monte Carlo integration Monte Carlo methods multiple-recursive Niederreiter nodes nonlinear congruential obtained optimal orthogonal arrays parameters particle per(x period length permutation point sets prime probability properties pseudorandom vectors quadrature quasi-Monte Carlo methods quasirandom quasirandom sequences random number random walk recursion s-dimensional s)-net in base s)-sequences sample Section simulated annealing Sobol solution statistical Theorem uniformly distributed unit cube upper bound variance