Open AccessNote—Optimal Inspection Policy in Sequential Screening
Author(s) -
June S. Park,
Michael Peters,
Kwei Tang
Publication year - 1991
Publication title -
management science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 4.954
H-Index - 255
eISSN - 1526-5501
pISSN - 0025-1909
DOI - 10.1287/mnsc.37.8.1058
Subject(s) - remainder , optimal stopping , computer science , bayesian probability , process (computing) , mathematical optimization , sampling (signal processing) , algorithm , mathematics , artificial intelligence , arithmetic , filter (signal processing) , computer vision , operating system
Under sequential screening, a production lot is inspected item-by-item; the decision is made after inspecting each item whether to inspect another item or to reject the remainder of the lot; and thus uninspected items are never accepted. This screening process is a special case of the sequential sampling considered in Wortham and Wilson (1971). The process is formulated as an optimal stopping problem using a Bayesian approach. Based on an analysis of the structural properties of the optimal policy, a backward-recursive optimal algorithm, which is more efficient than the existing algorithm for optimal sequential sampling, is developed.sequential screening, optimal stopping, Bayesian sequential decision process, dynamic programming