A Fuzzy Ahp Multi-Criteria Decision-Making Approach Applied to Combined Cooling, Heating, and Power Production Systems

Abstract

Most of the real-world multi-criteria decision-making (MCDM) problems contain a mixture of quantitative and qualitative criteria; therefore quantitative MCDM methods are inadequate for handling this type of decision problems. In this paper, a MCDM method based on the Fuzzy Sets Theory and on the Analytic Hierarchy Process (AHP) is proposed. This method incorporates a number of perspectives on how to approach the fuzzy MCDM problem, as follows: (1) combining quantitative and qualitative criteria (2) expressing criteria pair-wise comparison in linguistic terms and performance of the alternative on each criterion in linguistic terms or exact values when criterion is qualitative or quantitative, respectively, (3) converting all the assessments into trapezoidal fuzzy numbers, (4) using the difference minimization method to calculate the local weight of criteria, employing the algebraic operations of fuzzy numbers based on the concept of α-cuts, (4) calculating the global weight of criteria and the global performance of each alternative using geometric mean and the weighted sum, respectively, (5) using the centroid method to rank the alternatives. Finally, an illustrative example on evaluation of several combined cooling, heat and power production systems is used to demonstrate the effectiveness of the proposed methodology.

A Practical Approach for Evaluating and Prioritizing Situational Factors in Global Software Project Development

“…Hence, it has become famous for solving multi-attribute decision making (MADM) problems and providing a more precise ranking methodology [41]. All the steps involved in fuzzy AHP are the same as in AHP except for the fuzzy representation of the pairwise comparison by triangular fuzzy numbers (TFNs) [42].…”

Selection the optimal technology for electricity generation of 5 MW using a fuzzy multi-criteria decision-making approach

“…The local weight of a criterion is referred to the weight relative to other criteria at the same group and level, which is to be assessed using the pair-wise comparison process. The global weight of a criterion is referred to the weight relative to all other criteria for the overall objective of the decision problem [9].…”

“…Due to the fuzziness of the opinions and the wake transitivity restriction considered, we could not find an accurate solution for this problem. ω i could be calculated by minimization of the distance between υ ij obtained directly from the experts and the value υ' ij , [9] …”

“…As result, the original data evaluation criteria should be dimensionless and unit-free by normalization method [9]. As G ij is a benefit items,…”

Dynamic Fuzzy Logic Elevator Group Control System for Energy Optimization

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