Mustafa Acar

Date of Award

3-26-2015

Document Type

Thesis

Degree Name

Master of Science in Operations Research

Department

Department of Operational Sciences

First Advisor

Jeffery D. Weir, PhD.

Abstract

Many developed countries that have a combatant Air Force and Search & Rescue (SAR) assets designed for their Air Force's SAR service have been struggling with locating SAR units due to limited SAR assets, constrained budgets, logistic-maintenance problems, and high-risk level of military flights. In recent years, the Turkish Air Force (TUAF) has also been researching methods to gather all SAR units into a central base and deploying the needed number of SAR units to defined Deployment Points (DPs). This research applies three location optimization models to determine the optimum locations for TUAF SAR units. The first model, Set Covering Location Problem (SCLP), defines the minimum number of SAR DPs to cover all fighter aircraft training areas (TAs). The second model, Maximal Covering Location Problem (MCLP), aims to obtain maximum coverage with a given SAR DP number and response time. A weighted MCLP models is also applied with TAs risk values obtained by this research to maximize demanded coverage of TAs. Finally the last model, P-Median Location Problem, defines the locations of SAR DPs while obtaining minimum aggregate or average response time. These three models are applied via a Visual Basic for Applications (VBA) & LINGO Optimization Software interface that allows changing each exogenous variable of the models in a flexible way. The primary objective of this research is to provide the information for the required number of SAR units and their locations. The results indicate that the response time definition is as important as the required number of DPs. Additionally; some DP locations are indispensable because they have no alternative in their sectors.

AFIT Designator

AFIT-ENS-MS-15-M-148

DTIC Accession Number

ADA614919

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