DEVELOPMENT OF A NEW HYBRID MULTI CRITERIA DECISION-MAKING METHOD FOR A CAR SELECTION SCENARIO

Increasing competition in the automobile industry has led to a vast variety of choices when buying a car thus making car selection a tedious task. The objective of this research is to develop a new hybrid multi-criteria decision-making technique, with accuracy greater than that of the already existing methods, in order to help the people in decision-making while buying a car. Hence, considering a broader spectrum, this study aims at easing the process of multi-criteria decision-making problems in different fields. To achieve the objective, seven different alternatives were evaluated with respect to the enlisted evaluation criteria, which were selected after analyzing the secondary data obtained from Pak wheels based on style, fuel economy, price, comfort and performance. These criteria were then analyzed using the proposed Full Consistency Fuzzy TOPSIS method. As the name tells, this method is a unique combination of two techniques. The Full Consistency method is used to calculate the weights of the criteria while the Fuzzy TOPSIS approach is applied to rank the alternatives according to their scores in the selected criteria. The outcomes demonstrate an increase in the consistency ratio of the weight coefficients due to which the ranking of the alternatives by the FCF-TOPSIS is more accurate than the TOPSIS and the Analytical Hierarchy Process. The novelty of the method lies in the fact that this combination has not been used for an alternative selection scenario before. In addition to this, it can be used in various industries where a choice between the available alternatives arises based on a set of evaluation criteria

Integrated entropy-EDAS methods for the electrified car selection problem

Increasing air pollution affects the environment and life negatively. For a sustainable environment and life, people, voluntary organizations, and governments need to work on the solution of this problem. The biggest sources of air pollution are transportation vehicles. For this reason, many countries in Europe have stated that they will use solely electrified cars to reduce air pollution in the future. Therefore, in this study, it is aimed to determine the best electrified car. The result obtained can support consumers that to intend to buy an electrified vehicle in the decision-making process. This problem is a typical multi-criteria decision making (MCDM) problem and some MCDM techniques are used to solve these problems. Here, the Entropy method was used to determine the weights of the selection criteria. Selection criteria was determined according to comprehensive literature survey and interviews with sales representatives. The EDAS (Evaluation based on Distance from Average Solution) method was used to rank the electrified car alternatives that sold in Turkey. As a result of the evaluation, the most important criteria was determined by the price of the vehicle, the net battery capacity, and the electric motor power. According to these criteria, the electrified car manufactured in China was chosen as the best

A state-of-art survey on TQM applications using MCDM techniques

In today’s competitive economy, quality plays an essential role for the success business units and there are considerable efforts made to control and to improve quality characteristics in order to satisfy customers’ requirements. However, improving quality is normally involved with various criteria and we need to use Multi Criteria Decision Making (MCDM) to handle such cases. In this state-of the-art literature survey, 45 articles focused on solving quality problems by MCDM methods are investigated. These articles were published between 1994 and 2013.Seven areas were selected for categorization: (1) AHP, Fuzzy AHP, ANP and Fuzzy ANP, (2) DEMATEL and Fuzzy DEMATEL, (3) GRA, (4) Vikor and Fuzzy Vikor, (5) TOPSIS, Fuzzy TOPSIS and combination of TOPSIS and AHP, (6) Fuzzy and (7) Less frequent and hybrid procedures. According to our survey, Fuzzy based methods were the most popular technique with about 40% usage among procedures. Also AHP and ANP were almost 20% of functional methods. This survey ends with giving recommendation for future researches

Analysis of Decision Support Systems of Industrial Relevance: Application Potential of Fuzzy and Grey Set Theories

The present work articulates few case empirical studies on decision making in industrial context. Development of variety of Decision Support System (DSS) under uncertainty and vague information is attempted herein. The study emphases on five important decision making domains where effective decision making may surely enhance overall performance of the organization. The focused territories of this work are i) robot selection, ii) g-resilient supplier selection, iii) third party logistics (3PL) service provider selection, iv) assessment of supply chain’s g-resilient index and v) risk assessment in e-commerce exercises. Firstly, decision support systems in relation to robot selection are conceptualized through adaptation to fuzzy set theory in integration with TODIM and PROMETHEE approach, Grey set theory is also found useful in this regard; and is combined with TODIM approach to identify the best robot alternative. In this work, an attempt is also made to tackle subjective (qualitative) and objective (quantitative) evaluation information simultaneously, towards effective decision making. Supplier selection is a key strategic concern for the large-scale organizations. In view of this, a novel decision support framework is proposed to address g-resilient (green and resilient) supplier selection issues. Green capability of suppliers’ ensures the pollution free operation; while, resiliency deals with unexpected system disruptions. A comparative analysis of the results is also carried out by applying well-known decision making approaches like Fuzzy- TOPSIS and Fuzzy-VIKOR. In relation to 3PL service provider selection, this dissertation proposes a novel ‘Dominance- Based’ model in combination with grey set theory to deal with 3PL provider selection, considering linguistic preferences of the Decision-Makers (DMs). An empirical case study is articulated to demonstrate application potential of the proposed model. The results, obtained thereof, have been compared to that of grey-TOPSIS approach. Another part of this dissertation is to provide an integrated framework in order to assess gresilient (ecosilient) performance of the supply chain of a case automotive company. The overall g-resilient supply chain performance is determined by computing a unique ecosilient (g-resilient) index. The concepts of Fuzzy Performance Importance Index (FPII) along with Degree of Similarity (DOS) (obtained from fuzzy set theory) are applied to rank different gresilient criteria in accordance to their current status of performance. The study is further extended to analyze, and thereby, to mitigate various risk factors (risk sources) involved in e-commerce exercises. A total forty eight major e-commerce risks are recognized and evaluated in a decision making perspective by utilizing the knowledge acquired from the fuzzy set theory. Risk is evaluated as a product of two risk quantifying parameters viz. (i) Likelihood of occurrence and, (ii) Impact. Aforesaid two risk quantifying parameters are assessed in a subjective manner (linguistic human judgment), rather than exploring probabilistic approach of risk analysis. The ‘crisp risk extent’ corresponding to various risk factors are figured out through the proposed fuzzy risk analysis approach. The risk factor possessing high ‘crisp risk extent’ score is said be more critical for the current problem context (toward e-commerce success). Risks are now categorized into different levels of severity (adverse consequences) (i.e. negligible, minor, marginal, critical and catastrophic). Amongst forty eight risk sources, top five risk sources which are supposed to adversely affect the company’s e-commerce performance are recognized through such categorization. The overall risk extent is determined by aggregating individual risks (under ‘critical’ level of severity) using Fuzzy Inference System (FIS). Interpretive Structural Modeling (ISM) is then used to obtain structural relationship amongst aforementioned five risk sources. An appropriate action requirement plan is also suggested, to control and minimize risks associated with e-commerce exercises

A CLOUD TOPSIS MODEL FOR GREEN SUPPLIER SELECTION

Due to stringent governmental regulations and increasing consciousness of the customers, the present day manufacturing organizations are continuously striving to engage green suppliers in their supply chain management systems. Selection of the most efficient green supplier is now not only dependant on the conventional evaluation criteria but it also includes various other sustainable parameters. This selection process has already been identified as a typical multi-criteria group decision-making task involving subjective judgments of different participating experts. In this paper, a green supplier selection problem for an automobile industry is solved while integrating the Cloud model with the technique for order of preference by similarity to an ideal solution (TOPSIS). The adopted method is capable of dealing with both fuzziness and randomness present in the human cognition process while appraising performance of the alternative green suppliers with respect to various evaluation criteria. This model identifies green supplier S4 as the best choice. The derived ranking results using the adopted model closely match with those obtained from other variants of the TOPSIS method. The Cloud model can efficiently take into account both fuzziness and randomness in a qualitative attribute, and effectively reconstruct the qualitative attribute into the corresponding quantitative score for effective evaluation and appraisal of the considered green suppliers. Comparison of the derived ranking results with other MCDM techniques proves applicability, potentiality and solution accuracy of the Cloud TOPSIS model for the green supplier selection

Design of a Framework for Strategic Supplier Evaluation Decision

Abstract. The supplier evaluation process is a decision problem that has many criteria and goals that contain many qualitative and quantitative factors. So various multi criteria decision making (MCDM) techniques are widely used for supplier evaluation process. The process of evaluating and improving the performance of suppliers is very important to measure the effectiveness of management. The measurement and evaluation of the current system performance is indispensable to the organization for sustainable organizational growth. This research will make a framework of decision making to evaluate strategic suppliers. Output from evaluation of strategic supplier performance assessment considering sustainability criteria. Most research in evaluating only considers the assessment of supplier performance alone. The contribution of this research is to make a model of strategic supplier decision evaluation that considers not only the assessment on the supplier's performance but also how the assessment of the items supplied. The results of this study will be used to help automotive companies evaluate strategic supplier performance Keywords: strategic supplier, evaluation, decision making, sustainability

Suppliers Selection In Manufacturing Industries And Associated Multi-Objective Desicion Making Methods: Past, Present And The Future

Nowadays, many manufacturing companies have decided to use other companies’ competencies and outsource part of their manufacturing processes and business to suppliers globally in order to reduce costs, improve quality of products, explore or expand new markets, and offer better services to customers, etc. The decisions have rendered manufacturing organizations with new challenges. Organizations need to evaluate their suppliers' performance, and take account of their weakness and strength in order to win and survive in highly competitive global marketplaces. Hence, suppliers evaluation and selection are taken as an important strategy for manufactring enterprises. This paper aims to provide a comprehensive and critical review on suppliers selection and the formulation of different criteria for suppliers selection, the associated multi-objctive decision makings, selecion algorithms, and their implementation and application perspectives. Furthermore, individual and integrated suppliers selection approaches are presented, including Analytic hierarchy process (AHP), Analytic network process (ANP), and Mathematical programming (MP). Linear programming (LP), Integer programming (IP), Data envelopment analysis (DEA) and Goal programming (GP) are discussed with in-depth. The paper concludes with further discussion on the potential and application of suppliers selection approach for the broad manufacturing industry

Evaluating of effective factors on green supply chain management using statistical methods and SWARA approach

Major purpose of this research is identification and evaluating of effective factors on implementation of Green Supply Chain Management (GSCM) at Fanavaran Petrochemical Company by using statistical methods of Kolmogorov-Smirnov, mean and decision making method by topic SWARA (Stepwise Weight Assessment Ratio Analysis). Research methodology of present research base on purpose is practical and based on data gathering method is descriptive-measurement. In order to extracting the effective factors on GSCM at the company, in first, by literature review, 22 factors were identified. Then data were gathered by using of opinions of population members containing 55 persons of experts and senior managers in the first class of company. Finally, after analyzing the questionnaires and statistical tests above, 11 factors were confirmed and selected. In continues, in order to evaluating the final factors and ranking them base on importance in success implementation of GSCM system, the SWARA technique is used. Final outcome of this technique showed that second factor as “Designing products to reduce energy and material consumption, reuse and recycling of materials, prevent the use of hazardous materials in the production process” by most weight is extracted as the most important factor. Such, the factors of “Materials and compliance with the standards required for the purchase of raw materials” and “Procurement, distribution and reverse logistics” placed in next ranks base on importance. The factor of “total environmental quality management” by least weight is identified as last factor in implementation of GSCM at the company. In the end of research, it is proposed that organizations focus on environmental problem to acquire skill green environment advantage through green supply chain activities

Investigation on marine LNG propulsion systems for LNG carriers through an enhanced hybrid decision making model

Since the use of LNG as an alternative fuel has drawn increasing attention from the marine industry, this paper aimed to evaluate three competitive LNG fuelled engine systems: ultra-steam turbine, four-stroke medium speed engine, and two-stroke low-speed engine systems. To achieve this goal, the paper developed an enhanced hybrid decision-making model which was applied to integrate the economic, environmental and technical performance of these systems. This model can be represented as a semi-quantitative multi-criteria decision making process in combination of several novel techniques, particularly ‘life cycle cost assessment’ for economic analysis, ‘life cycle assessments’ for environmental analysis, ‘fuzzy order preference by similarity to ideal solution’ for technical analysis and ‘fuzzy analytic hierarchy process’ for multi-criteria decision making. A case study with a 174K LNG carrier has revealed that the two-stroke low-speed engine system is the most effective overall and suggested that this type of engine system will hold the lead over the other candidates in the large LNG carrier market. It has also demonstrated the effectiveness of the proposed model to improve the inherent subjectivity in existing qualitative multi-criteria decision-making processes by guiding the overall process in a more objective direction. Finally, this paper has revealed an underlying novelty of the proposed model to enhance the level of confidence level in the decision by expanding our short-term perspective to the holistic one