Top PDF Multi Criteria Decision Making Using ELECTRE

Our approach for validation of the project starts with selection of a project to assess the effectiveness of the method. After careful analysis, we have decided to take “Library Management System” as the pilot project. The standard set of requirements was identified after having done a detailed literature survey on the topic. In order to ascertain the effectiveness of the proposed method, we have associated ourselves with a web based development company. The project manager of the company was asked to do the project using his own view. In order to standardize it has been planned to have working hours from 9:00 AM to 4:00 PM with a break of 1 ½ hours lunch break in between. Also, after having discussion, it has been decided to use Visual Basic as front end and Ms– Access as backend. The results were recorded that include the number of days taken for completion, number of Lines of Code and customer satisfaction.

Multi-criteria decision making methods are extensively used in solving decision making problems, which is the process of choosing the optimal one among other alternatives. Among various alternatives, decision making process is defined as the selection of the appropriate one in our objectives. The process is encountered in every aspect of our daily lives. Due to the presence of more than one objective in decision making level and the continuous increase of the alternatives, multiobjective decision making methods are being used in almost all areas. Determining the financial performance of the enterprises and choosing the best performance is also considered as a decision making problem. As a result of literature studies, it has been found out that the most widely used multi-criteria decision making techniques in terms of applicability and interpretation are ELECTRE and TOPSIS methods. Therefore, these two methods have been chosen as study subjects.

computations compared with cross-efficiency analysis. Rao and Padmanabhan (2006) employed the diagraph and matrix methods for evaluating and ranking of the alternative robots for a given industrial application. Kahraman et al. (2007) developed a hierarchical fuzzy TOPSIS method to solve the multi-attribute robot selection problems. Karsak (2008) proposed a decision model for robot selection based on QFD and fuzzy linear regression methods while integrating the user demands with the technical characteristics of the robots. Chatterjee et al. (2010) applied two MCDM methods, i.e. VIKOR (VIse Kriterijumska Optimizacija kompromisno Resenje) and ELECTRE II (ELimination and Et Choice Translating REality) to solve robot selection problems. Kumar and Garg (2010) proposed a deterministic quantitative model based on distance-based approach for evaluation, selection and ranking of robots. Koulouriotis and Ketipi (2011) developed a fuzzy digraph method for robot evaluation and selection according to a given industrial application. Singh and Rao (2011) developed a hybrid decision-making technique combining graph theory and matrix approach, and AHP method. Kentli and Kar (2011) applied satisfaction function and a distance measure technique for solving the robot selection problems. Rao et al. (2011) proposed a subjective and objective integrated multiple attribute decision-making method for robot selection.

In recent years, many papers on facility location problems have been published. Many of those previous studies propose multi-criteria decision making (MCDM) techniques as a solution method. Considering that multiple criteria with imperfect and uncertain factors are involved, fuzzy based methods, such as, TOPSIS, VIKOR and ELECTRE I, (Zadeh, 1965) are commonly utilised as approaches to such MCDM problems. An overview of previous work on relevant MCDM studies is provided in Table 1, which covers the MCDM solution methods, particularly focusing on analytic hierarchy/network process, fuzzy ELCTRE I, Fuzzy TOPSIS and Fuzzy VIKOR, applied to given location selection problems. Hsu et al. (2012) presented an analytic network process (ANP) approach for the selection of potential sites for CO 2 geological storage.

the leading alternatives after eliminating the less favorable alternatives. A Preference Ranking Organisation Method (PROMETHEE) is another MCDM technique which uses the concept of outranking approach (Brans & Vincke,1985). The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), developed by Hwang and Yoon, is an alternative decision-making method of ELECTRE method. The basic concept used by this method is that the feasible selected alternative possesses the minimum distance from the ideal solution and the maximum distance from the negative-ideal solution. This method usually makes an assumption that each criterion has monotonically increasing or decreasing tendency, which becomes easy to locate the positive or negative ideal solutions (Hwang & Yoon,1981). The Euclidean distance method is then used to measure the distances of each alternative which sets the preference order for each alternative.

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. the solution that maximizes the cost criteria and minimizes the benefits criteria, and the shortest distance from the positive- ideal solution, i.e., the solution that maximizes the benefit criteria and minimizes the cost criteria. It is applied to find the better alternative when more number of conflicting criteria is available.

On the other hand, Portfolio management can be conducted in a number of ways, but the dominant approaches involve the application of some form of rational model(s) to evaluate and rank projects and monitor their progress. These functions are often assembled in an information system that makes it possible to automate the collection, calculation, and presentation of data. The information system or portfolio system is then expected to aid rational decision-making. Decision makers can be located at various levels and units in companies and the decision process can be organized in numerous ways, but in this project the research writer focused on AHP method in order to develop a process for rank the project risks when they are brought to the portfolio level. The output of this method brings the clear cut picture of the project issues prioritization for the management level in order to make crucial decision in the portfolio level.

The decision making problems with imprecise data has a special significance in real life problems. Here the concept of fuzzy soft sets which always possess parameterization tools is applied to solve a multi-observer multi-criteria decision making problem.

In order to reduce adverse effects on the environment caused by conventional (mass) Tourism, the importance of ecotourism is becoming increasingly highlighted as this form of tourism contributes to the environmental protection and sustainable development of an area. The main objective of this study is the development of a reliable model for the identification of zone suitability for sustainable development of ecotourism, which will represent a significant support for planners in strategy development and management of ecotourism. The proposed model is based on the combined application of Geographic Information Systems (GIS) and Multi-Criteria Decision Analysis (MCDA) using Fuzzy Decision Making Trial and Evaluation Laboratory (FDEMATEL) method in order to estimate and map the suitability classes of ecotourism potentials in the study area of Zhejiang Province (China). The model has been developed by using 11 criteria grouped in 3 clusters. The application FDEMATEL method has been used for expert calculation of the weight for all clusters/criteria in relation to their impact on the development of ecotourism. The final suitability map of ecotourism development has been obtained by applying Weighted Linear Combination (WLC) and it has been designed in 3 suitability classes as: Highly Suitable (S1), Moderately Suitable (S2), Marginally Suitable (S3), and Not Suitable (NS). The proposed method and the results of this study can be used as a policy of sustainable development at all levels of public administration.

Purchasing management is a department in an organization responsible for purchasing activities. Purchase is most important function in any organization. Purchase is the first element which efforts the product cost. People are interested and keen in selection of cars which have become essential and comfortable mode of travel. One of the most critical way is the selection of the best car. Multi Criteria Decision Making (MCDM) techniques namely Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), Fuzzy TOPSIS, Vlse Kriterijumska Optimizacija Kompromisno Resenje (VIKOR) are effectively applied in the selection process of cars.

method requires the pre-selection of a countable number of alternatives and the use of a countable number of quantifiable (conflicting and noncommensurable) perfor- mance attributes (criteria). The attributes (criteria) may indicate costs and benefits to a DM. A larger outcome always means greater preference for a benefit or less preference for a cost criterion. After inter and intra- comparison of the alternatives with respect to a given set of performance attributes (criteria), implicit/explicit trade-offs are established and used to rank the alternatives [20]. The AHP method is selected for its specificity, which offers a certain freedom to a DM to express his preferences for particular attributes (criteria) by using the original AHP measurement scale. The AHP method does not require such explicit quantification of attributes (criteria), but it needs specific hierarchical structuring of the MCDM problem. The method itself then generates the weights of the criteria by using the AHP measurement scale according to a specified procedure. Under such circu- mstances, a comparison of the results from such different methods applied to the same problem appears to be very interesting and challenging from both academic and practical perspectives. In the next sub- sections, the basic structures of three MCDM methods and the procedures for assigning weight to the attributes (criteria) are described [21]. Saaty [22-24] developed the following steps for applying AHP:

Where A1, A2, A3 .........., Am are possible alternatives among which decision makers have to choose, C1, C2, C3, ........., Cn are criteria with which alternatives performance are measured, xij is the performance value of alternatives Ai with respect to criterion Cj, wj is the weight of criterion Cj.

Analysis is primitive and foundation phase of the software development life cycle with its own role. Requirement analysis is a systematic approach which collects the stakeholder requirements from the different sources and converting into design specific. It is a socio technical for requirement gathering as well patterns of social interaction between user and requirement engineer. There is dominant impact of this phase is on the ftware product quality. The requirement engineering involved with various activities like understand the customer wants, analyzing its need, accessing its feasibility, negotiating of right solution and converting into operational system. The software projects have many requirements based on domain and its scope. The various of the system have many views on requirement. All the requirements not considerable to pursuable. The requirement engineer often face the complex situation where the decision making taken place in selection and prioritization of requirements from multiple on different criteria. The prioritization of requirements based feasibility study and necessity, it minimizes the stakeholder unsatisifaction and failureness of the software with intent of the quality. The errors formed in this phase will be continued to the later phases of the software development. The rectification of errors in this cost and time wise than the later stages of lytical Hierarchy Process is a suitable quantitative approach for such types of problems. This paper INTERNATIONAL JOURNAL

The quantifiable financial sub-criteria have been chosen based on the EIB’s emphasis on the CBA metrics of IRR, NPV, ERR and project cost. NPV and IRR are the two most common parameters used to compare investment projects. It is important to note that whilst these two metrics are strongly correlated, they provide two differing metrics, absolute value and percentage, commonly used in investment decisions. However, in a certain projects, the two criteria may give contradictory results, i.e. one project is acceptable if we consider the NPV method, but at the same time IRR method favours another project. The reasons of conflict between the two are due to the variance in the inflows, outflows, and life of the project. In these cases IRR is considered to be inappropriate. The ERR is an important factor in selecting projects, based on their value to society as a whole; EIB, as a policy driven Bank, considers this as essential to the decision making process. The fourth financial criterion is the initial cost of investment; obviously an essential metric in the process. This is especially the case for public investments which allocate tax revenue and where little or no monetary returns can be expected.

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.

A proposed method called RIMOORA in order to solve Group Decision Making problems. The proposed method determining the most preferable alternative among all possible alternatives, when performance ratings are described by rough interval. This method is very suitable for solving the group decision-making problem under rough interval environment. RIMOORA-GDM Method for Group Decision Making is shown in Fig. 1.

Chapter 4 will show the developed antifouling selection model and its algorithm. It also contains the established decision making data that will be used in the algorithm. The final Excel package that is used for the model together with its verification and validation results are shown as well.

KDD 99 is the benchmark dataset utilized to test the classification capabilities of classifiers. However, many classifiers generate similar results by measuring performance on various criteria. Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is a traditional multi-criteria decision making (MCDM) approach which is widely used to rank classifiers from number of options that are assessed on various criteria.

The decision support methods have been implemented in the various applications satisfying the constraints to the major extent. These methods came into existence in early 1960 and the work continued with the different application. The complexity in decision making, increased with the number of alternatives and the stakeholder involvement resulting in the implementation of MCDM. Depending on the functional requirement different techniques can be used for the attainment of the solution using either linear programming or non-linear programming or discrete optimization technique. Abbas Mardani et.al [4] published study on the MCDM techniques and their applications in Energy, environmental and sustainability, Operation research and soft computing, Knowledge management etc. Vaidya, O. S. & Kumar, S [5] shows survey on AHP used in Energy management, E-commerce, Government sectors etc. Achimugu P.et.al [6] gives details on a literature review of Software Requirements Prioritization. Vicent Penades-Pla et.al [7] work details about a review of Multi-Criteria Decision-Making Methods Applied to the Sustainable Bridge Design. This study mainly highlights MCDM application in different areas of software engineering from 2001 to 2018. The sources referred are IEEE, Science Direct, Research Gate, Conferences and Journals. Some of the applications are tabulated in Table I. and are discussed as follows.

Risk management is a combination of good management and decision making at all levels of an organization. It is not a new method, which have various standards and guidance documents are useable (ON 2008, IEC 2008, DGQ 2007, FAA 2007, Rio Tinto 2007, HB 2004, ACT 2004, AZ/NZS 2004). Risk acquaint in human daily lives, from private to public sector organizations but depends on the context such as environmental risk, hazardous waste, insurance, stakeholder, technical cause etc. In short risk can be defined as an uncertainty of the outcomes. There arefew researchers who explained, having risk as adverse outcomes. Risk is also explained as the uncertainty that covers future events and outcomes, which express as odds and impact of a case with the capacity to influence the achievement of an organization’s objectives. In some organizations risk management result in biased or unwanted consequences. There are two different safety management principles, the worse possible events at an installation should not have consequences outside certain boundaries claimed by effect based safety management and *Corresponding author: Amit Yadav