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.

Recently, a multi facility, multi product and multi period industrial problem has been widely investigated in Supply Chain Network(SCN). One of keys issues in the current SCN research area involves minimizing both production and distribution costs. This study deals with finding an optimal solution for minimizing the total cost of production and distribution problems in supply chain network. First, we presented an integrated mathematical model that satisfies the minimum cost in the supply chain. To solve the presented mathematical model, we used a genetic algorithm with an excellent searching ability for complicated solution space. To represent the given model effectively, the matrix based real-number coding schema is used. The difference rate of the objective function value for the termination condition is applied. Computational experimental results show that the real size problems we encountered can be solved within a reasonable time.

Supply chain is usually represented by a network (which is called supply chain network) that contains some nodes. In a supply chain network these nodes are suppliers, plants, distribution centers and customers which are some facilities connected by some arcs to each other. The arcs connect the nodes in the direction of their production flow, meaning that each arc shows a route between the facilities for transporting the products. A multi-stage supply chain network (MSCN) is defined as a sequence of multiple supply chain network stages. This paper addresses a typical supply chain network problem which is based on a two-stage single-product system under uncertain conditions such that both cost and constraint parameters are interval numbers. The combination of these uncertain parameters are considered in this typical problem for the first time. In this case, two different order relations (the order relations UC ≤ and HW ≤ ) for interval numbers are considered. Then, two solution procedures are developed in order relations for the interval two-stage supply chain network design problem. The efficiency of the proposed method is illustrated by a numerical example where it is proved that the relation HW ≤ shows better performance than the relation UC ≤ .

The competition between companies for prior occupation of the market is becoming fierce. In this highly competitive situation, it is important for companies to differentiate themselves if they are going to have a chance at success. And the competition to create the best solution method possible is higher than ever. Increased competition is forcing companies to lower costs and improve efficiency. A supply chain management(SCM) has become one of the most important solution methods of competitive advantage. This study has developed a simulator for the supply chain network problem. The simulator is designed to simulate the conditions of an actual supply chain network considering uncertainties. The simulator developed using commercial simulation tool ARENA and the results of computational experiments for a simple example were given and discussed to validate the developed simulator. Further research is needed, but using the simulator could become a useful tool for decision making in the supply chain network area.

최근 로봇의 제조 기술 및 로봇 움직임의 제어 기술이 축적되고 컴퓨터와 정보통신 기술이 비약적으로 성장하면서, 세계 각국은 새롭게 떠오르고 있는 로봇 산업을 국가적인 전략산업으로 규정하고 기술 개발에 매진하고 있는 상황이다. 로봇 산업계가 경쟁력을 갖추기 위해서는, 로봇을 생산하는 메이저 규모의 주도 기업과 해당 기업을 위하여 부품을 생산하는 협력 업체들이 모두 함께 기술을 개발을 하고 그 결과를 공유하면서 동시에 조직화적으로 발전해 나가야 한다. 이를 위해서는 로봇 산업계의 공급망을 구성하여야 하고, 공급망에서의 업무 프로세스가 정비되어야 하며, 기업 간 협력을 위한 체계와 방안을 마련하여야 한다. 본 연구는 로봇 산업계의 공급망 구성 방안을 설계함으로써, 기업 간 협력 체계를 제안하여 로봇 산업계의 생산 구조를 고도화할 수 있는 방안을 제시하고자 한다.

In an environment of global competition, the success of a manufacturing corporation is directly related to bow it plans and executes production in particular as well as to the optimization level of its process in general. This paper proposes a production

The aim of the paper is to solve the problem of customer reduction due to the difficulty of parts sourcing which impacts production delay and delivery delay in SC networks. Furthermore, this paper is to suggest the new inventory policy of MTS in order to solve the problem of current inventory policy. In order to compare two policies, a LCD maker is selected as a case study and the real data for 2007 years is used for simulation input. The maker uses MTO policy for parts sourcing which has the problem of lead time even if it has some advantage of inventory cost. Based on current process. The simulation program of AS-IS model and TO-BE model using ARENA 10 version is developed for evaluation. In a result, the order number of two policies shows that MTO is 52 and MTS is 53. However the quantity of order shows big difference such that MTO is 168,460 and MTS is 225,106. Particularly, the lead time of new inventory policy shows much shorter that that of MTO such that MTO 100 is days and MTS is 16 days. In spite of short lead time by MTS policy, new policy has to take burden of inventory cost per year. Total inventory cost per year by MTS policy is US 11,254 and each part inventory cost is that POL is US 1,807, LDI is US 2,166 and Panel is US 7,281. The implication of the research is that the company has to consider the cost and the service simultaneously in deciding the inventory policy. In the paper, even if the optimal point of deciding is put into tactical area, the ground of decision is suggested in order to improve the problem in SC networks.