UMD Theses and Dissertations

Permanent URI for this collectionhttp://hdl.handle.net/1903/3

New submissions to the thesis/dissertation collections are added automatically as they are received from the Graduate School. Currently, the Graduate School deposits all theses and dissertations from a given semester after the official graduation date. This means that there may be up to a 4 month delay in the appearance of a given thesis/dissertation in DRUM.

More information is available at Theses and Dissertations at University of Maryland Libraries.

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Author: search.filters.author.Mehta, KunalSubject: search.filters.subject.multi attribute decision making

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    Design and Comparison Of Sample Allocation Schemes For Multi-Attribute Decision Making
    (2018) Mehta, Kunal; Herrmann, Jeffrey; Systems Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    In case of multi-attribute decisions, when a decision maker has a limited budget for data collection, then the decision maker has to decide on the number of samples to observe from each alternative and its attributes. This allocation decision is of importance when the observation process is uncertain, such as with physical measurements. This thesis presents a sequential allocation approach in which measurements are conducted one at a time. Prior to making a measurement the decision-maker’s current knowledge of the attribute values is used to identify the attribute and alternative pair to sample next using all these allocation procedures. The thesis discusses a simulations study that was performed to compare the Sequential Allocation Approach, Proportional Allocation Approach and Uniform Allocation Approach. We evaluated the frequency of selecting the true best alternative when the attribute value observations contain discrete random measurement error. The results indicate that the sequential approach is significantly better than the other approaches when the budget is small; as the budget increases, its advantage decreases.