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MULTIPERIOD SEARCH MODELS FOR AN UNKNOWN NUMBER OF VALUABLE OBJECTS
Author(s) -
Luss Hanan
Publication year - 1975
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.1540-5915.1975.tb01032.x
Subject(s) - prior probability , computer science , bayesian probability , constraint (computer aided design) , poisson distribution , negative binomial distribution , mathematical optimization , promotion (chess) , econometrics , artificial intelligence , machine learning , mathematics , statistics , geometry , politics , political science , law
In this paper we examine multiperiod search models for cases in which the number of valuable objects is unknown. The objective is to maximize the expected total returns during the planning horizon, subject to an effort constraint. Using a Bayesian approach, we examine the model for three different priors for the number of valuable objects, and we show that the different priors (binomial, Poisson and negative binomial) lead to such conceptually different results as adaptive and nonadaptive optimal policies. The models can be applied to many areas including mineral explorations, marketing promotion activities and intelligence information.