Graduation Year

2005

Document Type

Dissertation

Degree

Ph.D.

Degree Granting Department

Industrial Engineering

Major Professor

Michael Weng, Ph.D

Committee Member

William Miller, Ph.D.

Committee Member

Tapas Das, Ph.D.

Committee Member

Ram M. Pendyala, Ph.D.

Committee Member

A.N.V. Rao, Ph.D.

Keywords

Best selection method, SAW, TOPSIS, Sensitivity analysis, AHP, Utility theory, Hierarchy of attributes

Abstract

For any given reason, every year many countries spend a lot of money purchasing at least one weapon. Due to the secret character of the military, the decision process for specific weapon procurement is shrouded. Moreover, there are several funds loss cases due to mistakes in weapon contractions. Weapon procurement requires very large amounts of money which comes from tax payers. Therefore, an effort to reduce a possible monetary loss is needed.

A decision process based on an analytic model can present a better chance to decision makers for better weapon decisions. In general, weapon procurement decision is a multi criteria environment. Decision making in such environments is defined as Multi-Criteria Decision Making (MCDM). MCDM is broadly classified into two areas: Multi-Attribute Decision Making (MADM) and Multi-Objective Decision Making (MODM).

MADM methods are used for selecting an alternative from a small explicit list of alternatives.MODM methods are used for designing problems involving an infinite number of alternatives implicitly defined by mathematical constraints. This research is intended to be used by the South Korean Navy when there is a need to select one weapon type among several candidate types. Therefore, MADM methods are used in this research.

Many researches for developing an analytical model for better decision-making have been done. However, there is no research for a generalized weapon procurement decision model that is easy to implement. For this reason, whenever there is a need for weapon procurement decision, the Navy has to spend a lot of effort in determining the best weapon. These efforts can be reduced with a generalized model that is proposed in this research for naval weapon procurement.

MADM methods determine alternatives ranking orders and the highest ranked alternative is the best one. Various MADM methods are used in computing the alternatives ranking scores.. However, there is no MADM method which can compensate individual values for an overall value. Our new MADM model can compensate for that. We also provide a sensitivity analysis to the solutions obtained by the proposed model. This new model is applied to a real problem in the South Korean Navy.

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