A multiobjective coverage-based model for Civilian search and rescue

A multiobjective coverage-based model for Civilian search and rescue

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Article ID: iaor201112746
Volume: 58
Issue: 3
Start Page Number: 167
End Page Number: 179
Publication Date: Apr 2011
Journal: Naval Research Logistics (NRL)
Authors: ,
Keywords: allocation: resources, simulation: applications, combinatorial optimization, programming: multiple criteria, heuristics: genetic algorithms
Abstract:

The Civil Air Search and Rescue Association (CASARA) is a Canada-wide volunteer aviation association that provides air search support services to the Canadian National Search and Rescue (SAR) program. As with any emergency service provider, the locations of CASARA units greatly impact their overall effectiveness. In this article, the optimal location of CASARA units is formulated as a multiobjective maximal covering location problem. The model addresses the objectives of maximizing the coverage, minimizing the number of units, and maximizing the backup coverage of SAR incidents within Canada. A multigender genetic algorithm is proposed to determine a set of nondominated CASARA location configurations. Results are compared with solutions found using commercial integer programming software. It is shown that the nondominated genetic algorithm solutions are near-optimal. These are determined in much less time than comparable solutions using commercial integer programming software.

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