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SAMPLING AS A SOLUTION METHODOLOGY
Author(s) -
Mabert Vincent A.,
Whybark D. Clay
Publication year - 1977
Publication title -
decision sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.238
H-Index - 108
eISSN - 1540-5915
pISSN - 0011-7315
DOI - 10.1111/j.1540-5915.1977.tb01075.x
Subject(s) - sampling (signal processing) , computer science , sampling design , acceptance sampling , basis (linear algebra) , quality (philosophy) , slice sampling , mathematical optimization , importance sampling , operations research , data mining , statistics , mathematics , sample size determination , monte carlo method , population , philosophy , demography , geometry , filter (signal processing) , epistemology , sociology , computer vision
This paper examines the use of sampling procedures as a solution methodology for large combinatorial problems. Three sampling strategies are investigated: random sampling (each alternative is equally likely), biased sampling (alternatives' probabilities are biased by specified criteria), and improvement sampling (alternatives' probabilities are dynamically changed based upon new information). These three methodologies are illustrated and compared on the basis of solution quality and computer time requirements.