MODELING STRATEGIES FOR THE SPATIAL SEARCH PROBLEM

Abstract

ABSTRACT 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.

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