An integrated fuzzy approach to solving multi-criteria decision making problems / Nor Hanimah Kamis

Multi-criteria decision making (MCDM). Method is a technique where alternatives or options are assessed based on a set of criteria. Criteria weights determination and ranking of alternatives are two important aspects in solving MCDM problems. The evaluation of criteria importance by decision makers and performance rating towards alternatives often involve subjective preferences, which are normally vague and imprecise. This study proposed an improvised algorithm in criteria weights determination based on consistent fuzzy preference relations (CFPR). CFPR requires only (n-l) pair-wise comparisons from a given n criteria as compared to other some existing pairwise-based comparison approaches. We improvised Herrera-Viedma's et. al (2004) algorithm by introducing fuzzy numbers to represent input values for the entries of decision matrix. However, application of fuzzy numbers in representing importance of criteria requires tedious calculation. Therefore, centroid-index formula (Chen & Chen, 2000, 2003) was utilized in order to transform fuzzy numbers into crisp values, which indirectly gives lesser computation. The generalized Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method by Wang and Lee (2007) with some modification on criteria weights determination procedure using our proposed algorithm was employed in ranking the alternatives. An example problem on new staff selection in the Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA (UiTM) Malaysia is given to demonstrate the computational parts of this proposed model. This model can be used as an alternative tool in solving MCDM problems

Decision support model for the selection of asphalt wearing courses in highly trafficked roads

The suitable choice of the materials forming the wearing course of highly trafficked roads is a delicate task because of their direct interaction with vehicles. Furthermore, modern roads must be planned according to sustainable development goals, which is complex because some of these might be in conflict. Under this premise, this paper develops a multi-criteria decision support model based on the analytic hierarchy process and the technique for order of preference by similarity to ideal solution to facilitate the selection of wearing courses in European countries. Variables were modelled using either fuzzy logic or Monte Carlo methods, depending on their nature. The views of a panel of experts on the problem were collected and processed using the generalized reduced gradient algorithm and a distance-based aggregation approach. The results showed a clear preponderance by stone mastic asphalt over the remaining alternatives in different scenarios evaluated through sensitivity analysis. The research leading to these results was framed in the European FP7 Project DURABROADS (No. 605404).The research leading to these results has received funding from the European Union Seventh Framework Programme (FP7/2007–2013) under Grant Agreement No. 605404

Analysis of Green Computing Strategy in University: Analytic Network Process (ANP) Approach

Strengths, Weaknesses, Opportunities and Threats (SWOT) analysis do not provide an analytical means to determine the importance of the identified factors of green computing strategy and implementation. Although the SWOT analysis successfully explores the factors, individual factors are usually described very generally. For this reason, SWOT analysis possesses deficiencies in the measurement and evaluation of green computing steps. Even though the analytic hierarchy process (AHP) technique eliminates these deficiencies, it does not allow for measuring the possible dependencies among the individual factors. The AHP method assumes that the green computing factors presented in the hierarchical structure are independent; however, this assumption may be inappropriate in light of certain situation. Therefore, it is important to utilize a form of SWOT analysis that calculates and takes into account the possible dependency among the factors. This paper demonstrates a process for quantitative SWOT analysis of green computing implementation that can be performed even when there is dependence among strategic factors. The proposed algorithm uses the analytic network process (ANP), which allows measurement of the dependency among the green computing implementation factors, as well as AHP, which is based on the independence between the factors. There are four alternatives: campus awareness program, computer procurement, increase in heat removal requirement, and increase in equipment power density for improving the implementation of green computing in campus. Dependency among the SWOT factors is observed to effect the strategic and sub-factor weights, as well as to change the strategy priorities. Based on ANC method, the best alternative for this implementation is computer procurement

A comparative study of multiple-criteria decision-making methods under stochastic inputs

This paper presents an application and extension of multiple-criteria decision-making (MCDM) methods to account for stochastic input variables. More in particular, a comparative study is carried out among well-known and widely-applied methods in MCDM, when applied to the reference problem of the selection of wind turbine support structures for a given deployment location. Along with data from industrial experts, six deterministic MCDM methods are studied, so as to determine the best alternative among the available options, assessed against selected criteria with a view toward assigning confidence levels to each option. Following an overview of the literature around MCDM problems, the best practice implementation of each method is presented aiming to assist stakeholders and decision-makers to support decisions in real-world applications, where many and often conflicting criteria are present within uncertain environments. The outcomes of this research highlight that more sophisticated methods, such as technique for the order of preference by similarity to the ideal solution (TOPSIS) and Preference Ranking Organization method for enrichment evaluation (PROMETHEE), better predict the optimum design alternative

On optimal completions of incomplete pairwise comparison matrices

An important variant of a key problem for multi-attribute decision making is considered. We study the extension of the pairwise comparison matrix to the case when only partial information is available: for some pairs no comparison is given. It is natural to define the inconsistency of a partially filled matrix as the inconsistency of its best, completely filled completion. We study here the uniqueness problem of the best completion for two weighting methods, the Eigen-vector Method and the Logarithmic Least Squares Method. In both settings we obtain the same simple graph theoretic characterization of the uniqueness. The optimal completion will be unique if and only if the graph associated with the partially defined matrix is connected. Some numerical experiences are discussed at the end of the paper

Multi crteria decision making and its applications : a literature review

This paper presents current techniques used in Multi Criteria Decision Making (MCDM) and their applications. Two basic approaches for MCDM, namely Artificial Intelligence MCDM (AIMCDM) and Classical MCDM (CMCDM) are discussed and investigated. Recent articles from international journals related to MCDM are collected and analyzed to find which approach is more common than the other in MCDM. Also, which area these techniques are applied to. Those articles are appearing in journals for the year 2008 only. This paper provides evidence that currently, both AIMCDM and CMCDM are equally common in MCDM