Multi-criteria resource evaluation and allocation models under deterministic and fuzzy environments
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Date
2009
Authors
Ignatius, Joshua
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Abstract
In almost all decision making problems, competition for scarce resources remain in its center. Models of various techniques have been developed under the ambit of multi –criteria decision making (MCDM). However, the subject maturity on the deterministic environment far surpasses their fuzzy counterpart, leaving a gap on how uncertainties are resolved in real world applications disappointing. Since a quick decision is always sought in practical terms, there is a tendency to view every resource evaluation exercise or allocation with the same view. Hence, the notion of every problem is a nail if one possesses only a hammer rings true for most real world decision making exercises.
To avoid this well trodden path, a few cases of real world nature that could highlight the nuances of resource evaluation and allocation decisions are brought to the forefront in this study. Serving this purpose, MCDM is split into multi-attribute decision making (MADM) and multi-objective decision making (MODM) problems with each illustrated under both deterministic and fuzzy environments. This allows the study to begin with a basic problem before progressing to cover more complex issues. As such, the thematic buildup of this research shows that as decision making complexity increases, there is a greater urgency to describe how the added uncertainty is modeled, treated and resolved.
The section on MADM begins with the AHP method and its application in fisheries project selection. It is followed by hybrid models of AHP-fuzzy TOPSIS and AHP-fuzzy PROMETHEE in the contexts of faculty funding allocation and service quality evaluation of training providers under fuzzy environment. The transition from deterministic to fuzzy environment shows that albeit rising complexity, practicality
has to be maintained, such as the need to alleviate biased inputs to promote transparency without being exposed to decision making fatigue.
With regards to MODM, the deterministic environment for combinatorial auction (CA) in transportation procurement is modeled with three techniques (weighted objectives method, preemptive goal programming and compromise programming). The modeling in fuzzy environment subsequently describes how imprecision in price and amount of loads are resolved in the transportation contexts. Nonetheless, this is not done before addressing their mathematical properties and testing out various fuzzy mathematical programming’s solving routines in the context of a supplier selection and a general forward CA. Lastly, the case on training provider selection embodies an integration between Fuzzy MADM and Fuzzy MODM concepts and techniques to form a logical structure for a resource allocation algorithm for decision making under uncertainty.
Description
PhD
Keywords
Mathematical science , Multi-criteria resource , Fuzzy environments