Multi-Criteria Decision Making

The goal of MCDM is to help the decision maker (DM) to make a choice among a finite number of alternatives or to sort or rank a finite set of alternatives in terms of multiple criteria. The widely used MCDM methods are Analytic Hierarchy Process (AHP), Grey Relational Analysis (GRA), ELECTRE (Elimination EtChoixTraduisant la REalite, Technique for the Order of Prioritization by Similarity to Ideal Solution (TOPSIS), VIKOR, etc. Among the different MCDM techniques, the most widely applied method is TOPSIS . It is one of the widely applied MCDM techniques to solve multi criteria decision making problem (Hwang and Yoon, 1981). It is based on the principle that the chosen alternative should have the longest distance from the negative-ideal solution, i.e.

DempstereSchafer theory; Probability Abstract The evidential reasoning (ER) algorithm for multi-criteria decision making (MCDM) performs aggregation of the assessments of multiple experts, one each for every attribute (or subsystem or criterion) of a given system. Two variants of ER are proposed, that handle a scenario where more than one expert assesses an attribute. The first algorithm handles the case of multiple experts who assess an attribute of a larger system. Experiments compare a modification of ER for this scenario which results in poorer detection. The second algorithm is used when experts have overlapping areas of expertise among the subsystems. A comparison is made with a variant of ER in the literature. Both algorithms are examples of novel ‘exclusive’ and ‘inclusive’ ER.

Keywords: Arithmetic mean, Multi Criteria Decision Making, Trapezoidal fuzzy number, Triangular fuzzy number, Value of fuzzy numbers, I. INTRODUCTION Most of the real life problems are complex in nature because of the indistinctness and impreciseness of the available data. In 1970 Bellman and Zadeh proposed the concept of fuzzy sets and fuzzy models to effectively handle these imprecise data which help us to avoid information loss through computing with words. To solve such real world problems, we can develop fuzzy expert systems by seeking the help of experts who have knowledge in that particular area. There may be many factors that influence a certain problem. While developing expert system, one has to rank these factors based on the experts’ judgements. Usually experts’

International Journal of Innovative Technology and Exploring Engineering (IJITEE) ISSN: 2278-3075, Volume-8, Issue-9S4, July 2019 Abstract: Multi-criteria decision making (MCDM) is a powerful operational model which are used to resolve decision making problems on the basis of different decision criteria. This approach has been widely used in many application fields by the decision makers to solve their problems. Although there exists different MCDM methods but the basic principle of MCDM method involves selection of criteria, selection of alternatives, selection of aggregation methods and weight criteria using these methods and finally evaluation of a set of alternatives performed based on criteria weights. This study presents a small description on the working principle and different methods of a Multi-criteria decision making and furthermore provides survey on their application in different fields.

5. Summary and Conclusions The current paper established an integrated, normative framework for an analysis of the multi-criteria decision-making process, by taking into consideration the following aspects: Intangible criteria, Bounded Rationality, a Multi-Dimensional Utility function, and the General Informativeness ratio. The proposed method may be useful for better understanding of several decision making situations, when intangible decision criteria are taken into consideration, for example, a decision on a content of new type of food product by weighting tastes, flavors, and healthfulness. Another example is in the healthcare area, when a patient should decide on a treatment by weighting safety, level of recovery, trends, and reputation.

This work is licensed under the Creative Commons Attribution International License (CC BY). http://creativecommons.org/licenses/by/4.0/ Abstract Requirements prioritization is one of the key factors in deciding the success of the project and hence the software industry. One of the major concerns in software prioritization techniques is that the existing ranking techniques have a very modest support to different criteria used by stakeholders to present their ranking. The current techniques are not suitable for arriving at an optimized view of multiple stakeholders using multiple criteria. This research analyzes the issues in existing techniques. A web based decision support model using ELECTRE as the method for pri- oritization is proposed. ELECTRE is a multi-criteria decision making model that is proved to be ef- fective in ranking several decision making problems. The proposed system takes input from mul- tiple stakeholders using 100-point method. An optimized ranking is obtained using ELECTRE me- thod. The developed system is validated using a pilot project and is found to be efficient in terms of saving cost of implementation and man-hours needed for implementation.

5. C ONCLUSION This paper proposes three different methods based on rough interval technique to determine the best alternative among the various alternatives. The proposed methods based on the SOWIA technique with modification for each proposed method .An illustrative example is given to show the results and to compare the performance of the three methods. Hence the proposed methods are more practical, realistic, comprehensive and applicable for any rough interval multi- criteria decision making problems and very simple to understand and easy to implement in comparison to other methods; that are always complex to comprehend and sometimes difficult to implement and the calculation processes are always ineffective when a new alternative is added or removed. The decision maker can easily apply RIMOORA method because of its several advantages such as highly stable, simple and easy to implement decision making approach with less mathematical calculations over other two MCDM methods such as (RIOCRA) and (RIARAS).The final ranking of alternatives is obtained by REGIME method.

The importance of a source is particularly crucial in hier- archical multi-criteria decision making problems, specially in the Analyltic Hierarchy Process (AHP) [16], [20]. That’s why it is primordial to show how the importance can be efficiently managed in evidential reasoning approaches. Of course if the fusion system designer wants to consider the importance as same as the reliability, it is his/her own choice, and in that particular case, the classical Shafer’s discounting technique can be applied. In general however, one must consider the importance and the reliability as two distinct notions and thus they have to be processed differently. Therefore the main question we are concerned here is how to deal with different importances of sources in the fusion process in such a way that a clear distinction is made/preserved between reliability and importance ?

Certificate of Approval This is to certify that the thesis entitled MULTI-CRITERIA DECISION MAKING APPROACH FOR VENDOR SELECTION submitted by Sri Utkarsh Yadav has been carried out under my supervision in partial fulfillment of the requirements for the Degree of Bachelor of Technology (B. Tech.) in Mechanical Engineering at National Institute of Technology, NIT Rourkela, and this work has not been submitted elsewhere before for any other academic degree/diploma.

Abstract Generally, the overall evaluation of a multi-criteria decision making (MCDM) problem is based on alternatives evaluations over a set of criteria and the weights of the criteria. However, in cases where the criteria weights are unknown, the overall evaluations cannot be derived. Therefore, several methods have been proposed to handle such MCDM problems. Nevertheless, there exist MCDM problems with small amount of data and poor information, which cannot be described by a probability distribution. In such MCDM problems, the applicability of existing approaches would be influenced. Accordingly, this manuscript investigates this type of MCDM problems with small amount of data and poor information, where information on criteria weights is unknown. To this end, a new hybrid MCDM is proposed; in which the unknown criteria weights are estimated using the maximizing deviation method with grey systems theory’s principles. Consequently, potential alternatives are evaluated and ranked by integrating degrees of possibility and PROMETHEE II.

Email: batton@emse.fr Email: smarand@unm.edu Abstract—In this paper, we present an extension of the multi- criteria decision making based on the Analytic Hierarchy Process (AHP) which incorporates uncertain knowledge matrices for generating basic belief assignments (bba’s). The combination of priority vectors corresponding to bba’s related to each (sub)- criterion is performed using the Proportional Conflict Redistribu- tion rule no. 5 proposed in Dezert-Smarandache Theory (DSmT) of plausible and paradoxical reasoning. The method presented here, called DSmT-AHP, is illustrated on very simple examples.

Abstract: ABC analysis is one of the most widely employed inventory classification techniques in organizations. However, ABC analysis is based on only single measurement called annual usage value, it has been recognized that other criteria are also important in inventory classification. Multi Criteria Decision making methods can be used to classify the inventory using multiple criteria. In this paper, three Multi Criteria Decision making methods such as SAW (Simple Additive Weighing method), TOPSIS (Technique of Order Preference by Similarity to an Ideal Solution) and Compromise programming are used to classify the inventory. And the results of each method are integrated using group decision making to get a single effective inventory classification result.

There are many problems in the world’s and MCDM is the tools to get the optimize solution of it. Many books were published on MCDM [2-6] to understand the methods and their procedure easily. [52] used AHP to get optimal solution for highway traffic signals. The tool MCDM is being used by many researchers in decision-making process to ensure the most appropriate alternative. They applied MCDM in many ways like [32,122], take the benefits of MAUT and TOPSIS to select the location of land, [54,110,163],uses DEA, Fuzzy GP, VIKOR for waste treatment.[65] applied CBR for finding bankrupt. [56,148,150] applied AHP, VIKOR for health monitoring system and health care system. [202] made a hybrid method by combining three methods including Affinity Diagram, AHP and fuzzy TOPSIS for the improvement of city sustainability by evaluating four city logistics initiatives. For project selection, applied AHP and ANP combination give the decision of project investment studied by [201]. The most famous tool of the multi-criteria decision making methods is the MAUT, AHP, and in recent combination of methods and fuzzy based decision are the methodology for solving complex decisions. It can be applied to business, real life problems, portfolio, governmental sectors and many more.

to achieve this goal, the criteria for IaaS provider selection were determined and then compared according to their importance. The candidate IaaS providers were selected to evaluate according to the predetermined criteria. In this study, the analytic hierarchy process (AHP) as the multi-criteria decision-making technique was used to compare these IaaS providers. This paper presented the AHP based decision-making model to select a suitable cloud service provider focused on the IaaS provider for companies’ users. The criteria and sub-criteria for the proposed decision-making model were introduced and identified by considering the characteristics of IaaS and they were determined and then compared according to their importance. The IaaS providers were selected to evaluate for the proposed model. In this study, we compared the five IaaS providers which are domestic and international providers and serviced in Korean cloud service market. The proposed IaaS provider selection methodology was applied successfully. The proposed methodology can be used for other cloud service providers selection or cloud service selection problems.

Keywords Multi-criteria Decision Making, AHP, TOPSIS, Project Selection 1. Introduction All organizations have to select the projects which are determined to pursue among numerous opportunities. One of the biggest decisions that any organizations are likely to make related to the projects which they would undertake.

Decision making and risk assessment are becoming a challenging task in oil and gas due to the risk related to the uncertainty and imprecision. This paper proposed a model for the risk assessment based on multi-criteria decision making (MCDM) method by integrating Fuzzy-set theory. In this model, decision makers (experts) provide their preference of risk assessment information in four categories; people, environment, asset, and reputation. A fuzzy set theory is used to evaluate likelihood, consequence and total risk level associated with each category. A case study is presented to demonstrate the proposed model. The results indicate that the proposed Fuzzy MCDM method has the potential to be used by decision makers in evaluating the risk based on multiple inputs and criteria.

Department of Mechanical Engineering Kanad Institute of Engineering and Management, Mankar, India Abstract— This article presents an overview of different selection techniques as per Multi criteria Decision making and their applications. Recent articles which are pertinent regarding MCDM are collected and analysed to find out which approach and areas is more common compare to the other applications.

Keywords Multi-criteria Decision Making, AHP, TOPSIS, Project Selection 1. Introduction All organizations have to select the projects which are determined to pursue among numerous opportunities. One of the biggest decisions that any organizations are likely to make related to the projects which they would undertake.

Fuzzy logic widely has utilized in MCDM methods to optimize MCDM methods and created an extended approach named FMCDM (Fuzzy Multi-Criteria Decision Making ). FMCDM is a subset of Intelligent MCDM. During search in ISI web of knowledge data base there are 100 studies which use fuzzy technique to extend MCDM methods, this number is incomparable with other AI techniques. These studies mostly use fuzzy MCDM for evaluation, ranking and selection of alternatives, the Fuzzy set theory helps to numerized linguistic variables which used by decision makers regarding alternatives and criteria importancies. As the scope of FMCDM is very vast so it’s impossible to survey all applications and methods in detail. Table.2 shows classification of articles according their applications.

Since existing tools and methods in material selection do not fully support designers during the preliminary design stages in which the designers encounter imprecise data (discrete or incomplete information) or in situations where material selection problems include intangible properties, multi-criteria decision making based on ordinal data (MCDM-BOD), which has root in linear assignment method, is proposed to rank the materials for a given engineering component.