Optimal Supplier Selection Model with Multiple Criteria: A Case Study in the Automotive Parts Industry

This research proposes a mathematical model for supplier selection for a case-study car seat manufacturer. This research is divided into 2 parts. The first part is the raw material supplier evaluation method using Analytic Hierarchy Process. This part weights the importance of main decision criteria and sub-decision criteria, complying with part makers’ satisfaction. The result from the first part is scores for each raw material supplier resulting from multiple evaluation criteria. The second part proposes a mathematical model for supplier selection using integer programming. The scores of each supplier from the first part will be considered along with raw material consumption to select the suitable raw material suppliers that maximize overall part makers’ satisfaction. The results from the first part of this research show that the most important criterion for supplier evaluation is cost, which is about 41%. Quality, Delivery, Service, and Risk factors are approximately 24%, 14%, 12% and 9%, respectively. The result from the second part shows that the model can effectively match material suppliers to part makers according to their preferences. Comparing with current situation, the satisfaction is increased by 26% with this proposed framework. It means the proposed model can help matching the right supplier to each part maker that can increase overall satisfactions for this case-study’s supply chain

Fuzzy Analytic Hierarchy Process Evaluation Method in Assessing Corrosion Damage of Reinforced Concrete Bridges

Effective method used to deal with the corrosion damage condition of any concrete bridge superstructure will help decision makers of bridge management agencies to better choose repair material, and optimize repair method. Simplified corrosion index (SCI) is a very useful and simple index to characterize the actual corrosion damage condition of a reinforced concrete bridge superstructure. In this paper, SCI is calculated by combining the Corrosion Damage Index (CDI), Environment Change Factor (ECF) and Material Vulnerability Factor (MVF). The Analytic Hierarchy Process (AHP) method is applied to decide the weight factors of CDI, ECF and MVF. The Fuzzy-AHP evaluation method is used in this study to deal with the fuzzy problem of differentiating the different levels of corrosion indicators and to determine the appropriate weight factors. The asymmetric nearness degree method is applied to re-analyze the evaluation vector from Fuzzy-AHP method to calculate the corrosion damage level based on all corrosion indicators. A numerical example was presented to demonstrate the procedure and the benefits of the AHP method, and the proposed Fuzzy-AHP approach, along with the asymmetric nearness degree method, in dealing with the fuzzy nature of SCI calculation problem

Location of Facility Based on Simulated Annealing and “ZKW” Algorithms

To cope with the facility location problem, a method based on simulated annealing and “ZKW” algorithm is proposed in this article. The method is applied to some real cases, which aims to deploy video content server at appropriate nodes in an undirected graph to satisfy the requirements of the consumption nodes with the least cost. Simulated annealing can easily find the optimum with less reliance on the initial solution. “ZKW” algorithm can find the shortest path and calculate the least cost from the server node to consumption node quickly. The results of three kinds of cases illustrate the efficiency of our method, which can obtain the optimum within 90 s. A comparison with Dijkstra and Floyd algorithms shows that, by using “ZKW” algorithm, the method can have large iteration with limited time. Therefore, the proposed method is able to solve this video content server location problem

Supplier evaluation and selection in fuzzy environments: a review of MADM approaches

In past years, the multi-attribute decision-making (MADM) approaches have been extensively applied by researchers to the supplier evaluation and selection problem. Many of these studies were performed in an uncertain environment described by fuzzy sets. This study provides a review of applications of MADM approaches for evaluation and selection of suppliers in a fuzzy environment. To this aim, a total of 339 publications were examined, including papers in peer-reviewed journals and reputable conferences and also some book chapters over the period of 2001 to 2016. These publications were extracted from many online databases and classified in some categories and subcategories according to the MADM approaches, and then they were analysed based on the frequency of approaches, number of citations, year of publication, country of origin and publishing journals. The results of this study show that the AHP and TOPSIS methods are the most popular approaches. Moreover, China and Taiwan are the top countries in terms of number of publications and number of citations, respectively. The top three journals with highest number of publications were: Expert Systems with Applications, International Journal of Production Research and The International Journal of Advanced Manufacturing Technology

A Modified TOPSIS Method Based on D

Multicriteria decision-making (MCDM) is an important branch of operations research which composes multiple-criteria to make decision. TOPSIS is an effective method in handling MCDM problem, while there still exist some shortcomings about it. Upon facing the MCDM problem, various types of uncertainty are inevitable such as incompleteness, fuzziness, and imprecision result from the powerlessness of human beings subjective judgment. However, the TOPSIS method cannot adequately deal with these types of uncertainties. In this paper, a D-TOPSIS method is proposed for MCDM problem based on a new effective and feasible representation of uncertain information, called D numbers. The D-TOPSIS method is an extension of the classical TOPSIS method. Within the proposed method, D numbers theory denotes the decision matrix given by experts considering the interrelation of multicriteria. An application about human resources selection, which essentially is a multicriteria decision-making problem, is conducted to demonstrate the effectiveness of the proposed D-TOPSIS method