A New Approach to Estimate the Critical Constant of Selection Procedures | Zendy

E. Jack Chen | Zendy; Min Li | Zendy

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A New Approach to Estimate the Critical Constant of Selection Procedures

Author(s) -

E. Jack Chen,

Min Li

Publication year - 2010

Publication title -

advances in decision sciences

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.178

H-Index - 13

eISSN - 2090-3367

pISSN - 2090-3359

DOI - 10.1155/2010/948359

Subject(s) - selection (genetic algorithm) , ranking (information retrieval) , monte carlo method , histogram , constant (computer programming) , computer science , mathematics , mathematical optimization , statistics , algorithm , artificial intelligence , image (mathematics) , programming language

A solution to the ranking and selection problem of determining a subset of size containing at least of the best from normal distributions has been developed. The best distributions are those having, for example, (i) the smallestmeans, or (ii) the smallest variances. This paper reviews various applicable algorithms and supplies the operating constants neededto apply these solutions. The constants are computed using a histogram approximation algorithm and Monte Carlo integration

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