A Pairwise Comparison Matrix Framework for Large-Scale Decision Making

abstract: A Pairwise Comparison Matrix (PCM) is used to compute for relative priorities of criteria or alternatives and are integral components of widely applied decision making tools: the Analytic Hierarchy Process (AHP) and its generalized form, the Analytic Network Process (ANP). However, a PCM suffers from several issues limiting its application to large-scale decision problems, specifically: (1) to the curse of dimensionality, that is, a large number of pairwise comparisons need to be elicited from a decision maker (DM), (2) inconsistent and (3) imprecise preferences maybe obtained due to the limited cognitive power of DMs. This dissertation proposes a PCM Framework for Large-Scale Decisions to address these limitations in three phases as follows. The first phase proposes a binary integer program (BIP) to intelligently decompose a PCM into several mutually exclusive subsets using interdependence scores. As a result, the number of pairwise comparisons is reduced and the consistency of the PCM is improved. Since the subsets are disjoint, the most independent pivot element is identified to connect all subsets. This is done to derive the global weights of the elements from the original PCM. The proposed BIP is applied to both AHP and ANP methodologies. However, it is noted that the optimal number of subsets is provided subjectively by the DM and hence is subject to biases and judgement errors. The second phase proposes a trade-off PCM decomposition methodology to decompose a PCM into a number of optimally identified subsets. A BIP is proposed to balance the: (1) time savings by reducing pairwise comparisons, the level of PCM inconsistency, and (2) the accuracy of the weights. The proposed methodology is applied to the AHP to demonstrate its advantages and is compared to established methodologies. In the third phase, a beta distribution is proposed to generalize a wide variety of imprecise pairwise comparison distributions via a method of moments methodology. A Non-Linear Programming model is then developed that calculates PCM element weights which maximizes the preferences of the DM as well as minimizes the inconsistency simultaneously. Comparison experiments are conducted using datasets collected from literature to validate the proposed methodology.Dissertation/ThesisPh.D. Industrial Engineering 201

A study on reducing digital piracy: an analytical network process approach with benefits, opportunities, costs and risks analysis

Dissertação para obtenção do Grau de Mestre em Engenharia e Gestão IndustrialThe world and the information technology in general has in recent years undergone a major transformation due to rapid technological innovations that became universally available to all. These innovations that are constantly being introduced bring an increasing ease of access, use, mobility and other gains which in turn are also facilitators to illegal activities, allowing for the acquisition of products that are identical to the original without there being any loss of quality in the copy process. This led to technologies that were created in order to prevent such practices of digital piracy and give more control to those who own the intellectual property rights, known as Digital Rights Management (DRM) technologies. The application of these technologies has brought new problems, such as excessive restrictions that do not satisfy consumers and may harm society in general by restricting the freedom of use and exchange of ideas. Although there is scientific work on this issue, there has never been applied a multi-criteria analysis to assist in the decision making of what could be the best solution to reduce digital piracy. By developing an analytical network process (ANP) model with analysis of benefits, opportunities, costs and risks (BOCR), this dissertation seeks to fill the gap in the scientific community with the implementation of a multi-criteria decision making process to determine the best alternative for this problem. Finally, in this dissertation there is also a practical application of the developed model in the national digital books area