Designing and Implementing Strategies for Solving Large Location-Allocation Problems with Heuristic Methods (91-10)

Abstract

Solution techniques for location-allocation problems usually are not a part of micro-computer based geo-processing systems. The large volumes of data to process and store and the complexity of algorithms present a barrier to implementation of these solution techniques in a micro-computer environment. Yet decision-makers need analysis systems that return solutions to location selection problems in real time. We show that processing requirements for the most accurate heuristic, location-allocation algorithm can be drastically reduced by pre-processing inter-point distance data as both candidate and demand strings and exploiting the spatial structure of location-allocation problems by updating an allocation table. Consequently, solution times increase approximately linearly with problem size. These developments allow the solution of large problems (3,000 nodes) in a microcomputer-based, interactive decision-making environment. These methods are implemented in a micro-computer system and tests on three network problems validate our claims.

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