• Journal of Information Technology Applications and Management
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• 제15권1호
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• pp.83-97
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• 2008

Today's competitive global market makes most enterprise endeavor to specialize their business areas, and co-operate with trading partners in supply chain by the forms of collaboration, information and business process sharing. However, even the supply chain plan generated by co-operation often fails to be executed successfully, because it was generated without capacities of suppliers and more over nested suppliers. To overcome this limitation, the supply chain plan of an enterprise should be generated truly integrated way. In this paper, we classify business patterns based on scenarios about quotation processing and supply chain planning in self-integrated environment. And we present business process models about four business patterns and describe them, which are classified by whether request for quotation includes information about price, required time periods, and quantity for each required time period and whether it is received from customer or sent to supplier. In addition, we describe the types of supply chain planning problem.

• 한국경영과학회지
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• 제28권2호
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• pp.1-15
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• 2003

This paper presents a new evolutionary algorithm to solve complex multi-level integration problems, which is called multi-level symbiotic evolutionary algorithm (MEA). The MEA uses an efficient feedback mechanism to flow evolution information between and within levels, to enhance parallel search capability, and to improve convergence speed and population diversity. To show the MEA's applicability, It is applied to the integrated planning of production and distribution in supply chain management. The encoding and decoding methods are devised for the integrated problem. A set of experiments has been carried out, and the results are reported. The superiority of the algorithm's performance is demonstrated through experiments.

• 한국전자거래학회지
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• 제9권1호
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• pp.105-122
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• 2004

정보기술의 발전은 비즈니스 환경을 변화시켜왔고, 이러한 변화는 공급사슬 내의 거래 당사자들 간의 비즈니스프로세스 변화에도 영향을 주었다. 이러한 변화에 대한 최근의 경향은 파트너들 간의 긴밀한 유대관계를 강조하고 있다. 하지만 이는 정보를 교환하거나 의사결정을 내리는 데에 있어 업무 담당자의 참여를 필요로 하여 의사소통의 시간적 단절을 유발하고, 실시간 내의 정보수집 및 의사결정을 불가능하게 만드는 문제를 안고 있다. 이러한 문제를 해 결하기 위해, 거래 기업간의 응용 프로그램의 자동 의사소통을 바탕으로 한 자동통합이라는 새로운 개념이 도입되고 있으며, 이러한 개념은 미래형 공급사슬 환경의 방향이 될 것이다. 본 연구에서는 자동 통합 환경과 이 환경 하에서의 공급사슬계획을 위한 비즈니스 프로세스 모델을 소개하고, 이러한 공급사슬계획의 효율적인 수립을 위하여 협상과정을 분석하여 협상 패턴을 제시하였으며, 제시된 협상 패턴을 비즈니스 시나리오에 통합시킴으로써 통합된 공급사슬계획에서 협상을 위한 비즈니스 프로세스 모델을 제시하였다.

• 지능정보연구
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• 제13권3호
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• pp.47-61
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• 2007

기업 운영에서 SCM (Supply Chain Management)의 중요성이 인식되면서 공급, 생산, 분배 등의 기능들을 통합적으로 관리하는 새로운 접근법의 필요성이 커지고 있다. 이 접근법은 여러 다른 기능들의 의사결정 문제를 하나의 통합된 최적화 모델로 분석하는 방법이다. 특히 공급사슬의 통합적인 운영을 위해서는 이전의 확정적 방법론 보다는 보다 구매자와 공급자의 관계를 유연하게 통합해 줄 수 있는 방법론이 필요하다. SCM은 대규모 문제이고 또한 다양한 내외 요인에 의해 기존의 설정된 계획 내용이나 상황이 항시 동적으로 변경될 수 있기에, 이들 정보를 통합 계획에 반영될 수 있도록 하여야 한다. 본 연구에서는 SCM의 핵심이 되는 생산계획과 분배계획 문제들을 효율적으로 통합할 수 있는 유전 알고리즘 (Genetic Algorithm)을 제시하고, 유전 알고리즘을 기반으로 동적 SCM을 위한 멀티 에이전트 시스템을 구현한다. 한편 통합계획 문제에서 유전 알고리즘을 통해 100%에 근접하는 최적해를 구하였고, 통합계획으로 얻은 결과와 통합 계획을 하지 않은 경우의 결과 값에서 큰 차이를 확인 할 수 있었다.

• 산업공학
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• 제21권3호
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• pp.343-353
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• 2008

Vendor-managed inventory(VMI) is a supply chain strategy to improve the inventory turnover and customer service in supply chain management. Unfortunately, many VMI programs fail because they simply transfer the transactional aspects of placing replenishment orders from customer to vendor. In fact, such VMI programs often degrade supply chain performance because vendors lack capability to plan the VMI operations effectively in an integrated way under the dynamic, complex, and stochastic VMI supply chain environment. This paper presents a decision support system, termed DSSV, for VMI in the retail supply chain. DSSV supports the market forecasting, vendor's production planning, retailer's inventory replenishment planning, vehicle routing, determination of the system operating parameter values, retailer's purchase price decision, and what-if analysis. The potential benefits of DSSV include the provision of guidance, solution, and simulation environment for enterprises to reduce risks for their VMI supply chain operations.

• 대한안전경영과학회지
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• 제22권4호
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• pp.65-74
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• 2020

Many of companies have made significant improvements for globalization and competitive business environment The supply chain management has received many attentions in the area of that business environment. The purpose of this study is to generate realistic production and distribution planning in the supply chain network. The planning model determines the best schedule using operation sequences and routing to deliver. To solve the problem a hybrid approach involving a genetic algorithm (GA) and computer simulation is proposed. This proposed approach is for: (1) selecting the best machine for each operation, (2) deciding the sequence of operation to product and route to deliver, and (3) minimizing the completion time for each order. This study developed mathematical model for production, distribution, production-distribution and proposed GA-Simulation solution procedure. The results of computational experiments for a simple example of the supply chain network are given and discussed to validate the proposed approach. It has been shown that the hybrid approach is powerful for complex production and distribution planning in the manufacturing supply chain network. The proposed approach can be used to generate realistic production and distribution planning considering stochastic natures in the actual supply chain and support decision making for companies.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회/대한산업공학회 2003년도 춘계공동학술대회
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• pp.14-20
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• 2003

Supply chain is the link that moves products between suppliers, manufactures, wholesalers, distribution, retailers and ended consumers. Supply chain management(SCM) is a way to supervise the flow of products, materials and information as they move along the supply chain. In the recent years, Most of the companies are in a hurry the introduction of SCM to obtain international competitiveness. The goal of SCM is to optimize the supply chain, which can not only reduce inventories, but may also create a higher profit margin for finished goods by giving customers exactly what they want. There are four major decision areas (location, production, inventory, transportation) in supply chain management, and there are both strategic and operational elements in each of these decision areas. This paper is concerned with the integrated production planning problem including not only the production cost but also the transportation cost in supply chains, and an efficient algorithm using genetic algorithm and quickest path method is presented to solve the problem.

• 산업공학
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• 제13권3호
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• pp.378-387
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• 2000

As the globalization of manufacturing companies continues, the scope of dependence between these companies and distributors, and other suppliers are growing very rapidly since no one company manufactures or distributes the whole product by themselves. And, the need to increase the efficiency of the whole supply chain is increasing. This paper deals with a multi-plant lot-sizing problem(MPLSP) which happens in a decentralized manufacturing system of a supply chain. In this study, we assume that the whole supply chain is driven by a single source of independent demand and many levels of dependent demands among manufacturing systems in the supply chain. We consider setup cost, transportation cost and time, and inventory holding cost as a decision factor in the MPLSP. The MPLSP is decomposed into two sub-problems: a planning problem of the whole supply chain and a lot-sizing problem of each manufacturing system. The supply chain planning problem becomes a pure linear programming problem and a Generalized Goal Decomposition method is used to solve the problem. Its result is used as a goal of the lot-sizing problem. The lot-sizing problem is solved using the CPLEX package, and then the coefficients of the planning problem are updated reflecting the lot-sizing solution. This procedure is repeated until termination criteria are met. The whole solution process is similar to Lagrangian relaxation method in the sense that the solutions are approaching the optimum in a recursive manner. Through experiments, the proposed closed-loop hierarchical planning and traditional hierarchical planning are compared to optimal solution, and it is shown that the proposed method is a very viable alternative for solving production planning problems of decentralized manufacturing systems and in other areas.

• Industrial Engineering and Management Systems
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• 제15권2호
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• pp.156-172
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• 2016

Complex and uncertain issues in supply chain result in integrated decision making processes in supply chains. So decentralized (distributed) decision making (DDM) approach is considered as a crucial stage in supply chain planning. In this paper, an uncertain DDM through coordination mechanism is addressed for a multi-product supply chain planning problem. The main concern of this study is comparison of DDM approach with centralized decision making (CDM) approach while some parameters of decision making are assumed to be uncertain. The uncertain DDM problem is modeled through fuzzy mathematical programming in which products' demands are assumed to be uncertain and modeled using fuzzy sets. Moreover, a CDM approach is customized and developed in presence of fuzzy parameters. Both approaches are solved using three fuzzy mathematical optimization methods. Hence, the contribution of this paper can be summarized as follows: 1) proposing a DDM approach for a multi-product supply chain planning problem; 2) Introducing a coordination mechanism in the proposed DDM approach in order to utilize the benefits of a CDM approach while using DDM approach; 3) Modeling the aforementioned problem through fuzzy mathematical programming; 4) Comparing the performance of proposed DDM and a customized uncertain CDM approach on multi-product supply chain planning; 5) Applying three fuzzy mathematical optimization methods in order to address and compare the performance of both DDM and CDM approaches. The results of these fuzzy optimization methods are compared. Computational results illustrate that the proposed DDM approach closely approximates the optimal solutions generated by the CDM approach while the manufacturer's and retailers' decisions are optimized through a coordination mechanism making lasting relationship.

• 경영과학
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• 제19권2호
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• pp.75-89
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• 2002

According to the fast-paced environment of information technology and improving customer services, the design activities of logistics systems improve customer centric services and delivery performance implementing e-logistics system. The fundamental design issues that arise in the delivery system planning are optimizing the system with minimum cost and maximum throughput and service level. This study is concerned with the integrated model development of delivery system with customer responsive service level for DCM, Demand Chain Management. We used a two-step approach for this study. First, we formulated the supply. center facility planning using stochastic set-covering problem and assigned the customers to the supply center using clustering algorithm. Second, we developed vehicle delivery planning for a supply center based on GIS, GIS-VRP. Also we developed a GUI-type computer program for proposed method for supply center problem using GIS and Geo-DataBase of Busan area. The computational results showed that the proposed method was very effective on a set of test problems.