NDLI: Optimal sequential inspection policies

Content Provider	Springer Nature Link
Author	Boros, Endre Goldberg, am Kantor, Paul B. Word, Jonathan
Copyright Year	2010
Abstract	We consider the problem of combining a given set of diagnostic tests into an inspection system to classify items of interest (cases) with maximum accuracy such that the cost of performing the tests does not exceed a given budget constraint. One motivating application is sequencing diagnostic tests for container inspection, where the diagnostic tests may correspond to radiation sensors, document checks, or imaging systems. We consider mixtures of decision trees as inspection systems following the work of Boros et al. (Nav. Res. Logist. 56:404–420, 2009). We establish some properties of efficient inspection systems and characterize the optimal classification of cases, based on some of their test scores. The measure of performance is the fraction of all cases in a specific class of interest, which are classified correctly. We propose a dynamic programming algorithm that constructs more complex policies by iteratively prefixing devices to a subset of policies and thereby enumerating all of the efficient (i.e., undominated) inspection policies in the two dimensional cost-detection space. Our inspection policies may sequence an arbitrary number of tests and are not restricted in the branching factor. Our approach directly solves the bi-criterion optimization problem of maximizing detection and minimizing cost, and thus supports sensitivity analysis over a wide range of budget and detection requirements.
Starting Page	89
Ending Page	119
Page Count	31
File Format	PDF
ISSN	02545330
Journal	Annals of Operations Research
Volume Number	187
Issue Number	1
e-ISSN	15729338
Language	English
Publisher	Springer US
Publisher Date	2010-10-22
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Dynamic programming Sequential inspection Bi-objective optimization Port security Combinatorics Theory of Computation Operations Research/Decision Theory
Content Type	Text
Resource Type	Article
Subject	Management Science and Operations Research

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