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A multiobjective coverage‐based model for Civilian search and rescue
Author(s) -
Asiedu Yaw,
Rempel Mark
Publication year - 2011
Publication title -
naval research logistics (nrl)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.665
H-Index - 68
eISSN - 1520-6750
pISSN - 0894-069X
DOI - 10.1002/nav.20387
Subject(s) - backup , integer programming , operations research , search and rescue , genetic algorithm , computer science , mathematical optimization , aviation , set (abstract data type) , software , service (business) , engineering , mathematics , business , algorithm , artificial intelligence , machine learning , database , operating system , marketing , robot , programming language , aerospace engineering
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. © 2009 Wiley Periodicals, Inc.* Naval Research Logistics, 2011