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APPLICATION OF ANALYTIC NETWORK PROCESS IN EVALUATING INITIAL TRAINING AIRCRAFT
Abstract
In this study, alternative trainer aircraft are evaluated and ranked according to the specific
criteria. Analytic Network Process is used as the multi-criteria decision making method. Five alternatives are chosen among popular trainers all around the world. Six main criteria and twentytwo sub-criteria are determined, so the solution matrix consists of twenty-seven columns and rows. Because of the complexity of the problem, a software called Super Decisions is used. Criteria are based on the ones used by flight instructors, managers of flight training organizations and researchers who are expert in this field. In the light of gathered data, criteria are weighted and alternative trainers are evaluated. Cirrus SR20 with 0.30 weight is estimated as the most feasible solution.
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This paper presents the methodology for assessing and selecting the most appropriate procedure for the preparation of nanoparticles by implementing the analytical network process. The commonly utilized nanoparticle preparation methods are Polymer Precipitation, Interfacial polymer deposition, Complex Coacervation, Cross linking, Emulsion solvent diffusion, Homogenization and Polymerization method. There are numerous parameters to be considered in groundwork of nanoparticles that departs the conclusion manufacturer in bias. One has to address a number of components in alignment to determine and choose the optimum conclusion choices, because an unsuitable conclusion could lead to the eventual merchandise having to be formulated and developed again. For this cause in this paper, we study selecting the most appropriate procedure for the preparation of nanoparticles utilizing one of the multi criteria-decision making techniques, Analytic Network Process.
The main goal was determined. The criteria and sub-criteria that affect the main goal were determined. The alternatives for the problem were determined. The interactions between criteria, sub-criteria, and alternatives respect to the main goal were determined. The super matrixes according to the network were assembled and then weighted super matrix and limit super matrix were then constructed. The values of this limit matrix are the desired priorities of the elements with respect to the goal. The alterative with the highest priority was finally chosen as the best alternative.
The emulsion solvent diffusion technique (M-5) has the highest value (0.434379) among the alternative methods that are applicable to the preparation of the nanoparticles. The second highest is Polymer Precipitation (M-1) with a value of 0.178798, and the lowest value or last choice is Cross Linking (M-4) with a value of only 0.024516. The alternative with the highest priority would achieve the goal, i.e., the best method for the preparation of the nanoparticles.
The alternative M5 emulsion solvent diffusion technique, scoring 0.434379 was the one with largest main concern amidst all the other alternatives and thereby judged to be the most apt procedure for the preparation of nanoparticles.
In recent years, intellectual capital (IC) has become the main asset of leading companies. Because the nature of intellectual capital is intangible and difficult to measure, it becomes a challenge for researchers to evaluate intellectual capital performance efficaciously. Different kinds of methods have been suggested to help managers evaluating performance of intellectual capital. Having analyzed past studies which have ignored the impressible state of intellectual capital indicators; a new model was proposed utilizing the analytic network process (ANP) method. The analytic hierarchy process (AHP) aims to formulate and prioritize the IC measurement indicators. Many decision-making problems cannot be structured hierarchically because they involve interaction of various factors. The analytic network process is a mathematical theory that can deal with all kinds of dependence systematically. The analytic network process is a general theory in the ratio scale that measures influence, based on a methodology that deals with dependence and feedback. ANP can be applied to analyze the interactive relations between factors with proper measurements of the weight for each factorial criterion. This paper presents esults of selected IC subcomponents and their dependencies in the most successful dairy company in Iran (Haraz Dairy).
In supply chain management, supplier selection can be treated as a type of hierarchical multi-criteria decision-making (MCDM) problems since it involves various criteria and hierarchical structure among criteria often exists. This paper investigates a kind of MCDM problems with two-level criteria and develops a novel hybrid method integrating TL-ANP (2-tuple linguistic analytic network process) and IT-ELECTRE II (interval 2-tuple Elimination and Choice Translating Reality II). Considering interactions among criteria, a TL-ANP approach, in which comparison matrices are consistent 2-tuple linguistic preference relations, is put forward to determine weights of criteria and sub-criteria. To deal with the case of criteria being not compensated, an IT-ELECTRE II approach is proposed. In this approach, ratings of alternatives on sub-criteria are represented as interval 2-tuple linguistic variables. A possible degree and a likelihood-based preference degree are respectively defined, followed by concordance, discordance and indifferent sets. Afterwards, concordance and discordance indices are identified and applied to establish net concordance and net discordance indices. Further, comprehensive dominant values of alternatives are obtained to rank alternatives. Thereby, a novel hybrid method is presented for MCDM with two-level criteria under interval 2-tuple linguistic environment. At length, a real case of supplier selection is examined and comparison analyses are conducted to illustrate the application and superiority of the proposed method.
Enterprise Resource Planning (ERP) system, which integrates all of the units within an organization at the information level, plays an important role for a successful enterprise. With the right ERP system, it is easier to provide coordination between the units, eliminate waste and make faster and better decisions. Adopting an ERP system is a significant investment decision for a firm, therefore a great deal of attention should be given to the selection of the right system. Since there are a large number of criteria to consider in selecting an ERP system, the process itself is regarded as a complex multi-criteria decision making problem. In this study, two prevalent multi-criteria decision making techniques, Analytic Network Process (ANP) and Preference Ranking Organization Method for Enrichment Evaluations (PROMETHEE), are used in combination to better address the ERP selection problem. First, ANP is used to determine the weights of all criteria, and then, the obtained weights are used in the PROMETHEE method for optimal ranking of the alternative system choices. To demonstrate the viability of the proposed methodology, an application case is performed on the ERP selection problem for the Small Medium Enterprises (SMEs) in İstanbul, Turkey. The proposed hybrid methodology successfully ranked the alternatives and identified the best ERP system based on the information obtained from a number of SMEs participated in this study.
The Analytic Network Process (ANP) is a general theory of relative measurement used to derive composite priority ratio scales from individual ratio scales that represent relative measurements of the influence of elements that interact with respect to control criteria. Through its superma-trix whose elements are themselves matrices of column priorities, the ANP captures the out-come of dependence and feedback within and between clusters of elements. The Analytic Hier-archy Process (AHP) with its dependence assumptions on clusters and elements is a special case of the ANP. The ANP is a new and an essential phase in decision making, neglected so far be-cause of the linear structures used in traditional approaches and their inability to deal with feed-back in order to choose alternatives not simply according to attributes and criteria, but also ac-cording to their consequences both positive and negative – an essential and so far a missing con-sideration in decision making. This paper gives a brief look at the foundation of the ANP to-gether with a simple example.
Multi-Criteria Decision Making (MCDM) techniques are gaining popularity in sustainable energy management. The techniques provide solutions to the problems involving conflicting and multiple objectives. Several methods based on weighted averages, priority setting, outranking, fuzzy principles and their combinations are employed for energy planning decisions. A review of more than 90 published papers is presented here to analyze the applicability of various methods discussed. A classification on application areas and the year of application is presented to highlight the trends. It is observed that Analytical Hierarchy Process is the most popular technique followed by outranking techniques PROMETHEE and ELECTRE. Validation of results with multiple methods, development of interactive decision support systems and application of fuzzy methods to tackle uncertainties in the data is observed in the published literature.
Most decision making requires the consideration of several conflicting objectives. The term multiple criteria decision analysis (MCDA) describes various methods developed for aiding decision makers in reaching better decisions. Energy planning problems are complex problems with multiple decision makers and multiple criteria. Therefore, these problems are quite suited to the use of MCDA. A multitude of MCDA methods exists. These methods can be divided in three main groups; value measurement models, goal, aspiration and reference level models, and outranking models. Methods from all of these groups have been applied to energy planning problems, particularly in the evaluation of alternative electricity supply strategies. Each of the methods has its advantages and drawbacks. However, we cannot conclude that one method generally is better suited than the others for energy planning problems. A good alternative might be to apply more than one method, either in combination to make use of the strengths of both methods, or in parallel to get a broader decision basis for the decision maker. Until now, studies of MCDA in energy planning have most often considered energy networks with only one energy carrier. More advanced energy systems with multiple energy carriers have been neglected, even though this field ought to be suitable for use of MCDA due to its high complexity, many decision makers and many conflicting criteria.
Various methods of consensus of preference rankings of individuals are described in applying group decision making. Here, we discuss two different approaches, one deterministic and the other stochastic. The first is applicable to situations where the group is small, and the second applies to opinions of the population at large where one cannot deal with people on an individual basis. The dividing line between these two approaches is not made in stone and it is the choice of the decision maker to select one approach or the other. How does one synthesize the judgments of a group? In these approaches we address the issues of obtaining priority weights for a group of individuals. Importance ranking of the judges is considered in the deterministic case.