• Journal of Korean Society of Industrial and Systems Engineering
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• v.32 no.3
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• pp.142-158
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• 2009

The supplier selection problem is perhaps the most important component of the purchasing function. Some of the common and influential criteria in the selection of a supplier include quality, price, delivery, and service. These evaluation criteria often conflict, however, and it is frequently impossible to find a supplier that excels in all areas. In addition, some of the criteria are quantitative and some are qualitative. Thus, a methodology is needed that can capture both subjective and objective evaluation measures. The Analytic Hierarchy Process(AHP) is a decision-making method for ranking alternative courses of action when multiple criteria must be considered. This paper proposes the AHP-based approach which can structure the supplier selection process and the achievements-based procedure which can allocate order quantities for the selected suppliers In automotive part manufacturers. Also, through the practical case of 'D' automotive part manufacturing company, we shows that the proposed AHP based supplier selection approach and the achievements-based allocation procedure of order quantity can be successfully applied for supplier selection and order quantity allocation problems.

• Journal of the Korea Safety Management & Science
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• v.13 no.4
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• pp.117-124
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• 2011

Supplier selection is one of the most important activities of a company. This importance is increased even more by new strategies in a supply chain, because of the key role suppliers perform in terms of quality, costs and services which affect the outcome in the buyer's company. In addition, green production has become an important issue for almost every manufacturer and will determine the sustainability of a manufacturer. Therefore a performance evaluation system for supplier and green suppliers is necessary to determine the suitability of suppliers to cooperate with the company. Supplier and green supplier selection is a multiple criteria decision making problem in which the objectives are not equally important. In practice, vagueness and imprecision of the goals, constraints and parameters in these problems make the decision making complicated. The objective of this study is to construct a decision-making process using fuzzy analytic hierarchy process (FAHP) and balanced scorecard (BSC) for evaluating supplier and green suppliers in the manufacturing industry. The BSC concept is applied to define the hierarchy with four major perspectives and performance indicators are selected for each perspective. FAHP is then proposed in order to tolerate vagueness and ambiguity of information. Finally, FAHP is applied to facilitate the solving process. With the proposed approach, manufacturers can have a better understanding of the capabilities that supplier and green supplier must possess and can evaluate and select the most suitable supplier for cooperation.

• Industrial Engineering and Management Systems
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• v.11 no.1
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• pp.1-10
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• 2012

Supplier selection is an essential task within the purchasing function of supply chain management because it provides companies with opportunities to reduce various costs and realize stable and reliable production. However, many companies find it difficult to determine which suppliers should be targeted as each of them has varying strengths and weaknesses in performance which require careful screening by the purchaser. Moreover, information required to assess suppliers is not known precisely and typically fuzzy in nature. In this paper, therefore, fuzzy multi-objective linear programming (fuzzy MOLP) is presented under fuzzy goals: cost minimization, service level maximization and purchasing risk. To solve the problem, we introduce an enhanced two-phase approach of fuzzy linear programming for the supplier selection. In formulated problem, Analytical Hierarchy Process (AHP) is used to determine the weights of criteria, and Taguchi Loss Function is employed to quantify purchasing risk. Finally, we provide a set of alternative solution which enables decision maker (DM) to select the best compromise solution based on his/her preference. Numerical experiment is provided to demonstrate our approach.

• Industrial Engineering and Management Systems
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• v.13 no.1
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• pp.29-42
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• 2014

Extensive research has been conducted on supplier evaluation and selection as a strategic and crucial component of supply chain management in recent years. However, few articles in the previous literature have been dedicated to the use of fuzzy inference systems as an aid in decision-making. Therefore, this essay attempts to demonstrate the application of this method in evaluating suppliers, based on a comprehensive framework of qualitative and quantitative factors besides the effect of gradual coverage distance. The purpose of this study is to investigate the applicability of the numerous measures and metrics in a multi-objective optimization problem of the supply chain network design with the aim of managing the allocation of orders by coordinating the production lines to satisfy customers' demand. This work presents a dynamic non-linear programming model that examines the important aspects of the strategic planning of the manufacturing in supply chain. The effectiveness of the configured network is illustrated using a sample, following which an exact method is used to solve this multi-objective problem and confirm the validity of the model, and finally the results will be discussed and analyzed.

• Industrial Engineering and Management Systems
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• v.11 no.2
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• pp.155-164
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• 2012

As the global market becomes more competitive, manufacturing industries face relentless pressure caused by a growing tendency of greater varieties of products, shorter manufacturing cycles and more sophisticated customer requirements. Efficient and effective supplier selection and order allocation decisions are, therefore, important decisions for a manufacturer to ensure stable material flows in a highly competitive supply chain, in particular, when customers are willing to accept products with less desirable product attributes (e.g., color, delivery date) for economic reasons. This paper attempts to solve optimally the challenging problem of supplier selection and order allocation, taking into consideration the customer flexibility for a manufacturer producing multi-products to satisfy the customers' demands in a multi period planning horizon. A new mixed integer programming model is developed to describe the behavior of the supply chain. The objective is to maximize the manufacturer's total profit subject to various operating constraints of the supply chain. Due to the complexity and non-deterministic polynomial-time (NP)-hard nature of the problem, an improved genetic approach is proposed to solve the problem optimally. This approach differs from a canonical genetic algorithm in three aspects: a new selection method to reduce the chance of premature convergence and two problem-specific repair heuristics to guarantee feasibility of the solutions. The results of applying the proposed approach to solve a set of randomly generated test problems clearly demonstrate its excellent performance. When compared with applying the canonical genetic algorithm to locate optimal solutions, the average improvement in the solution quality amounts to as high as ten percent.

• Industrial Engineering and Management Systems
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• v.8 no.4
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• pp.228-238
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• 2009

This paper first presents two supply chain design problems: 1) a factory location setting and factory selection problem, and 2) a factory location setting and factory/supplier selection problem. The first involves a number of location known retailers choosing one factory to supply their demands from a number of factories whose locations are to be determined. The goal is to minimize the transportation and manufacturing cost to satisfy the demands. The problem is then augmented into the second problem, where the procurement cost of the raw materials from a chosen material supplier (from a number of suppliers) is considered for each factory. Economic beneficial is taken into account in the cost evaluation. Therefore, the partner selections will influence the cost of the supply chain significantly. To solve these problems, an agent gaming and genetic algorithm hybrid method (AGGAHM) is proposed. The AGGAHM consecutively and alternatively enable and disable the advancement of agent gaming and the evolution of genetic computation. Computation results on solving a number of examples by the AGGAHM were compared with those from methods of a general genetic algorithm and a mutual frozen genetic algorithm. Results showed that the AGGAHM outperforms the methods solely using genetic algorithms. In addition, various parameter settings are tested and discussed to facilitate the supply chain designs.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.4
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• pp.112-119
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• 2017

Selecting suppliers in the global supply chain is the very difficult and complicated decision making problem particularly due to the various types of supply risk in addition to the uncertain performance of the potential suppliers. This paper proposes a multi-phase decision making model for supplier selection under supply risks in global supply chains. In the first phase, the model suggests supplier selection solutions suitable to a given condition of decision making using a rule-based expert system. The expert system consists of a knowledge base of supplier selection solutions and an "if-then" rule-based inference engine. The knowledge base contains information about options and their consistency for seven characteristics of 20 supplier selection solutions chosen from articles published in SCIE journals since 2010. In the second phase, the model computes the potential suppliers' general performance indices using a technique for order preference by similarity to ideal solution (TOPSIS) based on their scores obtained by applying the suggested solutions. In the third phase, the model computes their risk indices using a TOPSIS based on their historical and predicted scores obtained by applying a risk evaluation algorithm. The evaluation algorithm deals with seven types of supply risk that significantly affect supplier's performance and eventually influence buyer's production plan. In the fourth phase, the model selects Pareto optimal suppliers based on their general performance and risk indices. An example demonstrates the implementation of the proposed model. The proposed model provides supply chain managers with a practical tool to effectively select best suppliers while considering supply risks as well as the general performance.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2000.10a
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• pp.99-102
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• 2000

In the supply chain network design, how to select the best location, capacity configuration of the suppliers and to assign manufacturers orders are a challenging issue. Especially when multi-tiers'suppliers are existed, the performance of supply chain is influenced by 2$\^$nd/ and 3$\^$rd/ suppliers. Supplier selection is multi-criteria problem which includes both qualitative and quantitative factors in supply chains. In order to select the best supplier it is necessary to make a trade off between these two factors such as cost, product quality, capacity, production lead time, deliver lead time and transportation lead tine of supplier constraints existed in multi-tiers supplier purchasing chain. In these circumstances, purchasing agents should decide two problems: which is the best supplier in each tier and how much should be purchased from each selected supplier. This research is intended to develop an integration of an analytical hierarchy process (AHP) and mathematical modeling proposed to consider two factors which may be conflicted in choosing the best supplier in each tier and placing the optimum order quantities to the supplier among multi-tiers suppliers.

• Journal of the Korean Dietetic Association
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• v.8 no.1
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• pp.1-8
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• 2002

The purpose of this study is to clarify success factors for desirable relationship between buyer and supplier in elementary school. Therefore, the survey questionnaire consisted of general background, past success, success difference, buyer-supplier relationship characteristics(trust, supporting status, communication behavior, conflict resolution techniques, supplier selection process). The subjects were 66 dieticians of elementary school in Inchon. The statistical analysis of data was completed using SPSS program. The results were summarized as follows : Average total cost/day per one person ￦1,156. The number of suppliers per one school were 6. 92.3% of the subjects were in favor of private contract, regarding contract methods of purchasing food materials. For the past success, degree of satisfaction about past their supplier showed 3.49 score. The present success difference was shown higher than the past success. There was significant correlation between the past success and the present success difference. Trust about suppliers showed 3.40score. Supplying companies hardly support for buying school. Among information quality(timely, accurate, adequate, complete, credible), timely and complete showed lower score than the other kind of elements. Among the buyer-supplier relationship characteristic elements, only trust correlated with satisfaction about suppliers significantly. Among the conflict resolution techniques, joint problem solving and persuasive attempts were often made use of by subjects. The supplier selection criteria were shown quality(7.47), supplier's capabilities(6.46), management plan(6.00), price(5.73), scale(5.48), assets(5.27), considers delivery(4.76) and technology(2.39). As results, trust was needed for the desirable relationship between buyers and suppliers. This study has some limitations. The data in this study were collected from only buyer. It is more desired to acquire data from suppliers also.

• International Journal of Quality Innovation
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• v.8 no.2
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• pp.20-31
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• 2007

Moral hazard and adverse selection often exist in asymmetric information environment. In this paper, quality investment decision problem is studied under moral hazard. A basic model for quality investment level decision is developed with the supplier as a principal and the buyer as an agent. And then we regard the supplier and the buyer's rational limitations to set up a model when the buyer's quality evaluation and processing activities are hidden. The model is optimized and the results under different backgrounds are discussed and compared. Results show that the buyer's quality evaluation level and processing level are mostly influenced by the supplier's quality assurance payment. Both the supplier and the buyer choose different quality investment levels under moral hazard because of the supplier's payment to the buyer in case of internal failure and external failure.