An Efficient Method for Generating Discrete Random Variables with General Distributions
ACM Transactions on Mathematical Software (TOMS)
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
The Art of Computer Programming, 2nd Ed. (Addison-Wesley Series in Computer Science and Information
The Art of Computer Programming, 2nd Ed. (Addison-Wesley Series in Computer Science and Information
Markovian workload modeling for Enterprise Application Servers
C3S2E '09 Proceedings of the 2nd Canadian Conference on Computer Science and Software Engineering
Coresets and sketches for high dimensional subspace approximation problems
SODA '10 Proceedings of the twenty-first annual ACM-SIAM symposium on Discrete Algorithms
ACM Transactions on Graphics (TOG) - SIGGRAPH 2012 Conference Proceedings
Optimization via gradient oriented polar random search
Proceedings of the Winter Simulation Conference
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Let xi be a random variable over a finite set with an arbitrary probability distribution. Improvements to a fast method of generating sample values for xi in constant time are suggested. The proposed modification reduces the time required for initialization to O(n). For a simple genetic algorithm, this improvement changes an O(g n 1n n) algorithm into an O(g n) algorithm (where g is the number of generations, and n is the population size).