Intelligent Tool for Decision Making Associated With Hospitalization and Sandstorms for the Optimization of Ambulances

Intelligent Tool for Decision Making Associated With Hospitalization and Sandstorms for the Optimization of Ambulances

Estrella D. Molina-Herrera (University of Texas at El Paso, USA), Luis Ernesto Cervera-Gómez (El Colegio de Chihuahua, Mexico) and Carlos Herrera (University of Texas at El Paso, USA & El Paso VA Health Care System, USA)
DOI: 10.4018/978-1-5225-8131-4.ch003

Abstract

The shortest path problem is a typical problem of optimization. This chapter presents an innovative model associated with the use of case-based reasoning to solve a problem of routing vehicles in a Hospital of El Paso, United States. In this chapter, diverse components are described to characterize this problem through the use of a knowledge system. The algorithm was developed in Java, thus obtaining a tool which determines the best tracks to the vehicles associated with ambulances. An experiment was realized to probe the validations; the results were used to compare it with the Dijkstra algorithm and determine the quality of the results. The future research of this intelligent tool is to determine an innovative perspective related to episodic knowledge applied to resolution of diverse ambulances, and as this topic is determinative to find and remember the best solutions quickly, additionally the authors compare it with a code from other postgraduate students trying to implement an algorithm similar to logistics but using a shuffled frog leap algorithm.
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Descriptions Of The Model Components

In this section, we offer details of each component related to the application domain that is involved in the problem, in our case we solve a Logistics problem related to the El Paso Health System’s Hospitals using a bioinspired algorithm to create routes of vehicles to attend emergencies.

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