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A Study of Multicriteria Decision Making for Supplier Selection in Automotive Industry  [PDF]
Nadia Jamil,Rosli Besar,H. K. Sim
Journal of Industrial Engineering , 2013, DOI: 10.1155/2013/841584
Abstract: This paper is designed to present the effectiveness of group multicriteria decision making in automotive manufacturing company focusing on the selection of suppliers in Malaysia. The process of selecting suppliers is one of the most critical and challenging endeavor in any supply chain management. There are five decision making tools being analyzed in this study, namely, analytical hierarchy process (AHP), fuzzy analytical hierarchy process (FAHP), technique for order performance by similarity to ideal solution (TOPSIS), fuzzy technique for order performance by similarity to ideal solution (FTOPSIS), and fuzzy analytical hierarchy process integrated with fuzzy technique for order performance by similarity to ideal solution (FAHPiFTOPSIS). The scores of ranking among the suppliers in each MCDM tools (AHP, FAHP, TOPSIS, FTOPSIS, and FAHPiFTOPSIS) show significantly comparable variation. Scores of the best supplier is then compared to the lowest supplier for all MCDM tools whereby this reflects that the highest percentage goes to TOPSIS with scoring of 79.37%. On the contrary, FAHPiFTOPSIS demonstrated the lowest score variation of 22.42% which indicates that FAHPiFTOPSIS is able to eliminate biasness in supplier selection process. 1. Introduction A supply chain is a system which connects several departments from procurement of raw materials, to manufacturing, warehousing, and distribution of the products to the customers. Part of the contribution to supply chain complexity is the geographical outsourcing for cheaper supply and new market penetration. The complexity of supply chain is aggravated further when industry rely too much on multirange products and frequent introduction of new products as a strategy to meet different segmented market demands. In automotive industry, such situation is rampant. The frequent introduction of new models and shorter product lifecycles compounded by fast order-delivery require high level of agility and flexibility of the suppliers, thereby, exacerbating the supply chain complexity. Hence, the right selection of supplier becomes more complicated. With the mounting complexity of supply chain, the selection of the suppliers becomes very challenging. The recent incident in Fukushima, Japan, devastated by massive earthquake and nuclear disaster, and major floods in Thailand, had affected severely many Malaysian industries as well as industries in other parts of the world [1]. Those Malaysian companies which have their suppliers associated with these companies have suffered critical production problems, in particular,
Supplier Selection Based on Intuitionistic Fuzzy Sets Group Decision Making  [cached]
Lei Wen,Rui Wang,Wei Zhao
Research Journal of Applied Sciences, Engineering and Technology , 2013,
Abstract: The selection of suppliers had always been a key point of the supply chain management, directly impact the operation of supply chain. In this context, firstly introduced the study situation of supplier selection, established the evaluation index system based on the research and then puts forward a new method for supplier selection based on intuitionistic fuzzy sets. Finally, using an example to illustrate the application of indicators and the method provides a new method for supplier selection.
Supplier Selection Application Based on a Fuzzy Multiple Criteria Decision Making Methodology  [PDF]
Hüseyin Sel?uk KILI?
AJIT-e : Online Academic Journal of Information Technology , 2012, DOI: 10.5824/1309‐1581.2012.3.001.x
Abstract: Due to the increasing competitiveness in every sector of business life, being effective in every process of the organizations has been required. At this point, one of the most important processes is supplier selection process within the concept of supply chain management. If a systematic supplier selection methodology is performed, it will be possible to select the most suitable supplier and provide efficiency with respect to time, quality and cost. With this study, depending on the vague structure of the real working environment, an extensively used multi criteria decision making methodology TOPSIS is used within fuzzy environment. The proposed technique is applied in a real case and the most suitable suppliers are determined and ranked.
Fuzzy Similarity in Multicriteria Decision-Making Problem Applied to Supplier Evaluation and Selection in Supply Chain Management  [PDF]
Pasi Luukka
Advances in Artificial Intelligence , 2011, DOI: 10.1155/2011/353509
Abstract: It is proposed to use fuzzy similarity in fuzzy decision-making approach to deal with the supplier selection problem in supply chain system. According to the concept of fuzzy TOPSIS earlier methods use closeness coefficient which is defined to determine the ranking order of all suppliers by calculating the distances to both fuzzy positive-ideal solution (FPIS) and fuzzy negative-ideal solution (FNIS) simultaneously. In this paper we propose a new method by doing the ranking using similarity. New proposed method can do ranking with less computations than original fuzzy TOPSIS. We also propose three different cases for selection of FPIS and FNIS and compare closeness coefficient criteria and fuzzy similarity criteria. Numerical example is used to demonstrate the process. Results show that the proposed model is well suited for multiple criteria decision-making for supplier selection. In this paper we also show that the evaluation of the supplier using traditional fuzzy TOPSIS depends highly on FPIS and FNIS, and one needs to select suitable fuzzy ideal solution to get reasonable evaluation. 1. Introduction The overall objective of supplier selection process is to reduce purchase risk, maximize overall value to the purchaser, and build the closeness and long-term relationships between buyers and suppliers [1]. With the globalization of the economic markets and the development of information technology, many companies consider that a well-designed and implemented supply chain management (SCM) system is an important tool for increasing competitive advantage [2]. Previously, many methods have been proposed to solve the supplier selection problem, some of the popular ones being the linear weighting methods (LW) [3, 4], the analytic hierarchy process (AHP) [5, 6], the analytic network process [7], total cost approaches [8, 9], and mathematical programming (MP) techniques [10, 11]. However, several influence factors are often not taken into account in the decision-making process, such as incomplete information [12, 13], additional qualitative criteria, and imprecision preferences. A strategic approach towards supplier selection often involves multiple criteria [14] and several decision-makers [15, 16], and decision-making is often influenced by uncertainty in practice. Supplier selection may involve several and different types of criteria, combination of different decision models, group decision-making, and various forms of uncertainty. Technique for order performance by similarity to ideal solution (TOPSIS) [17], which is one of the known classical MCDM methods,
Group Decision Making Process for Supplier Selection with TOPSIS Method under Interval-Valued Intuitionistic Fuzzy Numbers  [PDF]
Mohammad Izadikhah
Advances in Fuzzy Systems , 2012, DOI: 10.1155/2012/407942
Abstract: Supplier selection is a fundamental issue of supply chain area that heavily contributes to the overall supply chain performance, and, also, it is a hard problem since supplier selection is typically a multicriteria group decision problem. In many practical situations, there usually exists incomplete and uncertain, and the decision makers cannot easily express their judgments on the candidates with exact and crisp values. Therefore, in this paper an extended technique for order preference by similarity to ideal solution (TOPSIS) method for group decision making with Atanassov's interval-valued intuitionistic fuzzy numbers is proposed to solve the supplier selection problem under incomplete and uncertain information environment. In other researches in this area, the weights of each decision maker and in many of them the weights of criteria are predetermined, but these weights have been calculated in this paper by using the decision matrix of each decision maker. Also, the normalized Hamming distance is proposed to calculate the distance between Atanassov's interval-valued intuitionistic fuzzy numbers. Finally, a numerical example for supplier selection is given to clarify the main results developed in this paper. 1. Introduction Supplier selection, the process of finding the right suppliers who are able to provide the buyer with the right quality products and/or services at the right price, at the right time, and in the right quantities, is one of the most critical activities for establishing an effective supply chain. Selecting the wrong supplier could be enough to deteriorate the whole supply chains financial and operational position. In todays highly competitive, global operating environment, it is impossible to produce low-cost, high-quality products successfully without satisfactory suppliers [1, 2]. The success of a supply chain is highly dependent on selection of good suppliers. Supplier selection is a fundamental issue of supply chain area that heavily contributes to the overall supply chain performance. Particularly for companies that spend a high percentage of their sales revenue on parts and material supplies and whose material costs represent a larger portion of total costs, savings from supplies are of particular importance. These strongly urge for a more systematic and transparent approach to purchasing decision making, especially regarding the area of supplier selection. Selecting the suppliers significantly reduces the purchasing cost and improves corporate competitiveness, and that is why many experts believe that the supplier selection
Supplier Selection Problem Based on Interval Intuitionistic Fuzzy Multiattribute Group Decision Making  [PDF]
Danyi Song, Jiao Wang
Open Journal of Business and Management (OJBM) , 2019, DOI: 10.4236/ojbm.2019.73103
Abstract: Aiming at the supplier selection problem where the decision information is an interval intuitionistic fuzzy number and completely does know the attribute and decision maker’s weight, this problem is reduced to a multi-attribute group decision problem. A decision method based on information entropy to determine the decision-maker’s weight and the deviation maximization method to determine the attribute weight is proposed. Finally, this method is applied to the selection of automotive parts suppliers, and the results are compared with the relevant methods, which fully illustrates the effectiveness of this method.
Feature of decision-making on purchases and choice of supplier during innovative activity
O.M. Iastremska,V.O. Pismak
Marketing ì Mened?ment Innovacìj , 2012,
Abstract: In article the basic actions of the enterprise during purchasing activity, feature of purchasing centers work organization are considered, it is offered to use during innovative activity three kinds of relations with suppliers: periodic, partner, integration according to level of suppliers appeal which is expedient for determining quantitatively on three groups of parameters: an economic situation of the supplier, conditions and consequences of cooperation with him.
A multiple criteria decision making technique for supplier selection and inventory management strategy: A case of multi-product and multi-supplier problem  [PDF]
Morteza Parhizkari,Maghsoud Amirib,Morteza Mousakhani
Decision Science Letters , 2013, DOI: 10.5267/j.dsl.2013.04.003
Abstract: Selection of an appropriate supplier along with planning a good inventory system has become an area of open research for the past few years. In this paper, we present a multi objective decision making supplier and inventory management model where two objectives including the quality and offering price of supplier are minimized, simultaneously. The proposed model is formulated as mixed integer programming and it is converted into an ordinary single objective function using Lp-Norm. In order to find efficient solution, we use NSGA-II as meta-heuristic technique and the performance of the proposed model is examined using some instances. The preliminary results indicate that both Lp-Norm and NSGA-II methods can be used to handle problems in various sizes.
A review of multi-criteria decision making techniques for supplier evaluation and selection
Prince Agarwal,Manjari Sahai,Vaibhav Mishra,Monark Bag
International Journal of Industrial Engineering Computations , 2011,
Abstract: Supplier evaluation and selection has been a vital issue of strategic importance for long time. Different multi-criteria decision making (MCDM) approaches have been proposed by the researchers in past, to solve the supplier evaluation and selection problem. In this paper, we present a review of various MCDM methodologies reported in the literature for solving the supplier evaluation and selection process. The review is solely based on sixty-eight research articles, including eight review articles in the academic literature from 2000 to 2011. We try to find out the most prevalent approach in the articles and thereby present the future scope of arriving at an optimal solution to the problem, based on the specifications, the strategies and the requirements of the buyers. The study presents that with the change in processes and the requirements, how the approach of the manufacturing industry has shifted from striving for operational effectiveness to the strategic partnership in the dyadic relationship.
A Multi-criteria neutrosophic group decision making metod based TOPSIS for supplier selection  [PDF]
R?dvan ?ahin,Muhammed Yi?ider
Computer Science , 2014,
Abstract: The process of multiple criteria decision making (MCDM) is of determining the best choice among all of the probable alternatives. The problem of supplier selection on which decision maker has usually vague and imprecise knowledge is a typical example of multi criteria group decision-making problem. The conventional crisp techniques has not much effective for solving MCDM problems because of imprecise or fuzziness nature of the linguistic assessments. To find the exact values for MCDM problems is both difficult and impossible in more cases in real world. So, it is more reasonable to consider the values of alternatives according to the criteria as single valued neutrosophic sets (SVNS). This paper deal with the technique for order preference by similarity to ideal solution (TOPSIS) approach and extend the TOPSIS method to MCDM problem with single valued neutrosophic information. The value of each alternative and the weight of each criterion are characterized by single valued neutrosophic numbers. Here, the importance of criteria and alternatives is identified by aggregating individual opinions of decision makers (DMs) via single valued neutrosophic weighted averaging (IFWA) operator. The proposed method is, easy use, precise and practical for solving MCDM problem with single valued neutrosophic data. Finally, to show the applicability of the developed method, a numerical experiment for supplier choice is given as an application of single valued neutrosophic TOPSIS method at end of this paper.
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