As Humanitarian Assistance and Disaster Relief (HADR) operations gain importance, a number of problems become evident. The time-sensitive problem of evacuating non-ambulatory people from a disaster area proves to be a challenging combinatorial optimization problem. The scope of the problem is defined by drawing analogies to similar vehicle routing problems that have been previously addressed. Based on the basic Max-Min Ant System (MMAS) algorithm modeled after the behavior of ants seeking food, potential solution approaches to this problem are enhanced to improve quality and efficiency by hybridizing features such as a best solution list, elite ants, ranked contribution system, and heuristic procedures during route construction. Using a Nearly-Orthogonal Latin Hypercubes (NOLH) experimental design, the algorithm parameters are tuned for best empirical performance for a range of test scenarios.
Apte, Aruna Heath, Susan
Master of Business Administration
Graduate School of Business & Public Policy (GSBPP)
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This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. As such, it is in the public domain, and under the provisions of Title 17, United States Code, Section 105, is not copyrighted in the U.S.
Internet Archive Python library 1.8.1
Lieutenant Commander, United States Navy Ministry of Defense, Singapore