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MODELING STRATEGIES FOR THE SPATIAL SEARCH PROBLEM
Author(s) -
Miller Harvey J.
Publication year - 1993
Publication title -
papers in regional science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.937
H-Index - 64
eISSN - 1435-5957
pISSN - 1056-8190
DOI - 10.1111/j.1435-5597.1993.tb01863.x
Subject(s) - pruning , monte carlo method , computer science , curse of dimensionality , mathematical optimization , machine learning , data mining , mathematics , statistics , agronomy , biology
Spatial search is a highly complex decision problem, hi this paper, modeling approaches are developed which alleviate some of the difficulties encountered in analyzing spatial search. A search modeling framework is outlined which states the problem in a sufficiently detailed yet manageable format. Within the framework, an operational model is developed which generates the probability that a feasible search pattern will result in the lowest realized acquisition cost. Solution strategies for the model include Monte Carlo simulation and a pruning rule which can reduce the dimensionality of the problem. Computational experience with the Monte Carlo procedure and the pruning rule is also provided.