• 대한안전경영과학회지
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• 제3권3호
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• pp.77-86
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• 2001

An operational strategy for inventory control on finished goods in the distribution system has been given attention to many enterprises and many studies regarding this field have been done and is also on-going currently. Many of these studies represented a large scale distribution network with a unified formulation by using defined symbols. These methods have provided the systematic approach of the distribution network but they are impossible to applying the reality system due to not considering the service rate of demand and treating the shortage of inventory. In order to overcome these unrealistic problems, the novel safety stock policy of responding to customers' inventory distribution network is suggested. this paper explores the transportation between Central Distribution Center(CDC) and Regional Distribution Center(RDC). Especially, the relation of transportation cost between CDC and RDC and cost of inventory control according to safety inventory with service level are emphasized. We could obtain the good results of this study by determining the optimal safety stock considering the various variables and constraints.

• Journal of applied mathematics & informatics
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• 제20권1_2호
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• pp.327-343
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• 2006

A general methodology is suggested to solve shelf-space allocation problem of retailers. A multi-item inventory model of breakable items is developed, where items are either complementary or substitute. Demands of the items depend on the amount of stock on the showroom and unit price of the respective items. Also demand of one item decreases (increases) due to the presence of others in case of substitute (complementary) product. For such a model, a Contractive Mapping Genetic Algorithm (CMGA) has been developed and implemented to find the values of different decision variables. These are evaluated to have maximum possible profit out of the proposed system. The system has been illustrated numerically and results for some particular cases are derived. The results are compared with some other heuristic approaches- Simulated Annealing (SA), simple Genetic Algorithm (GA) and Greedy Search Approach (GSA) developed for the present model.

• 산업공학
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• 제13권3호
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• pp.424-430
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• 2000

Supply chain management (SCM) is an area that has recently received a great deal of attention in the business community. While SCM is relatively new, the idea of coordinated planning is not. During the last decades, many researchers have investigated multi-stage inventory problems. However, only a few papers address the problem of cost-optimal coordination of multi-stage inventory control with respect to service measures. Even published approaches have a shortcoming in dealing with a delivery lead time consisted of a shipping time and a waiting time. Assumed that there is no waiting time, or that the delivery lead time is implicitly compounded of a shipping time and a waiting time, the problem is often simplified into a multi-stage buffer allocation and a single-stage stochastic buffer sizing problem at all installations. This paper presents a simulation-based heuristic algorithm and a comparison with others for the problem that cannot be decomposed into a multi-stage buffer allocation and a single-stage stochastic buffer sizing problem because the waiting time ties together all stages. The comparison shows that the simulation-based heuristic algorithm performs better than other approaches in saving average inventory cost for both Poisson and Normal demands.

• 한국경영과학회지
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• 제31권3호
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• pp.11-25
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• 2006

Space may be a scarce resource in manufacturing shops, warehouses, freight terminals, and container terminals. This Paper discusses how to locate temporary storage Inventories In limited storage areas. A typical inventory is delivered from the location of the preceding process to the storage area and stored In the storage area during the certain period of time. And it may be relocated from the storage position to another. Finally. it is delivered from the final storage area to the location of the next process. Because this logistic process for an inventory requires handling activities, transportation activities, and storage spaces, the limitation in capacities of handling equipment, transportation equipment, and storage space must be considered when allocating spaces to the inventory. This problem Is modeled as a multicommodity minimal cost flow problem. And a heuristic algorithm for the Problem is proposed. Numerical experiments are presented to validate the mathematical model and the heuristic algorithm.

• 경영과학
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• 제29권1호
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• pp.153-168
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• 2012

Order allocation is one of the most important decision-making problems of firms having significant influences on performances of themselves and the whole supply chain. Existing researches about order allocation have mainly focused on evaluating capabilities of directly connected suppliers so that it is hard to consider effects and interactions from undirected connections over multiple lower-layers. To alleviate the limitation, this paper proposed a novel approach to order allocation using structural hole. By applying the concept of structural hole to the supply network, we could evaluate the structural supplying powers of firms with respect to both of direct and indirect connections. In the proposed approach, we derived a methodology to measure the potential supplying power of each firm by modifying the effective size as one of the measurements of structural hole and then, proposed its application, the structural hole based order allocation strategy. Furthermore, we conducted the agent based modeling of supply chain to perform the decision-making process of order allocation and simulated the proposed strategy. As a results, by coping with the variance of demand more stably, it could improve the performance of supply chain from the aspects of fill rate, inventory level and demand-supply balance.

• 산업경영시스템학회지
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• 제5권6호
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• pp.1-6
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• 1982

The objective of this thesis to Provide a better insight into the effect of the amount of in-process storage has on the efficiency of production line with variable operation times. It is assumed that the material enters the line at the first work station and is then processed progressively through the line until it exits at the last work station, a finite amount of in-process storage is provided before all but the first work station of the line and the operation time of the work stations are statistically independent and follow exponential distribution. Under the above assumption, optimum allocation model is developed and following two approaches are used : 1) Given the available storage capacity, optimum allocation which minimizes the number of items in the line. 2) Given the available storage capacity, optimum allocation which. maximizes the utilization factor of the line. In a balanced three stage line, the production line efficiency is maximized under both categories when the second in-process storage is larger than the first.

• 한국경영과학회지
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• 제28권1호
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• pp.1-10
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• 2003

A recent trend In flexible manufacturing systems (FMS) Is to utilize the Identical versatile machines with fast tool delivery devices. Unlike a conventional FMS where parts are fed to the machines with the required tools, tools are acquired from other machines using a tool delivery system and parts can be finished on the same machine In these FMS. Therefore it Is more important problem 4o plan tool flow using tool delivery system In these FMS rather than part flow In conventional FMS. According to the existing study, In FMS 20∼30 percent of the total management cost Is the cost related with tools and It Is possible to reduce the tool Inventory by 40 percent using efficient tool allocation. In this study, In FMS under dynamic tool allocation strategy, a new method of part release considering tool flow at the stage of part release Is proposed. In order to prove the efficiency of the proposed part release It is compared with other part release through simulation experiments. Performance measures in these experiments are the throughput and the number of tardy parts.

• 대한산업공학회지
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• 제33권3호
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• pp.322-328
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• 2007

Highly standardized products are suitable for automated purchasing using electronic commerce technology, where the price becomes the most important factor. Suppliers can change the prices dynamically based on the inventory level and market situation in order to maximize the sales and profit. In the virtual marketplace where multiple customers purchase multiple standardized products from multiple suppliers repetitively, customers can purchase the required amount of each item as a dynamic bidding by allocating purchase orders to the suppliers based on the current price. Customers need a method to quickly determine the optimal allocation of orders to the suppliers using the dynamically changing data to minimize the total cost. We present a LP model which minimizes the sum of the total price plus transportation cost for this problem. Simulation results using random data show meaningful reduction of the total cost.

• Industrial Engineering and Management Systems
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• 제6권2호
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• pp.136-145
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• 2007

The selection of suppliers and the determination of order quantities to be placed with those suppliers are important decisions in a supply chain. In this research, a non-linear mixed integer programming model is presented to select suppliers and determine the order quantities. The model considers the purchasing cost which takes into account quantity discount, the cost of transportation, the fixed cost for establishing suppliers, the cost for holding inventory, and the cost of receiving poor quality parts. The capacity constraints for suppliers, quality and lead-time requirements for the parts are also taken into account in the model. Since the purchasing cost, which is a decreasing step function of order quantities, introduces discontinuities to the non-linear objective function, it is not easy to employ traditional optimization methods. Thus, a heuristic algorithm, called particle swarm optimization (PSO), is used to find the (near) optimal solution. However, PSO usually generates initial solutions randomly. To improve the PSO solution quality, a heuristic procedure is proposed to find an initial solution based on the average unit cost including transportation, purchasing, inventory, and poor quality part cost. The results show that PSO with the proposed initial solution heuristic provides better solutions than those with PSO algorithm only.

• 시스템엔지니어링학술지
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• 제13권1호
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• pp.79-88
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• 2017

For the PBL contract, it is necessary for the contracting parties to share information regarding the reasonable inventory-level and the cost of its repair parts for the estimated demand. There are various models which can be used for this purpose. Among them, V-METRIC model is considered to be the most efficient and is most frequently applied. However, this model is usually used for optimizing the inventory level of the repair parts of the system under operation. The model uses a time series forecast model to determine the demand rate, which is a mandatory input factor for the model, based on past field data. However, since the system at the deployment stage has no operational performance record, it is necessary to find another alternative to be used as the demand rate of the model application. This research applies the V-METRIC model to find the optimal inventory level and cost estimation for repairable items to meet the target operational availability, which is a key performance indicator, at the time of the PBL contract for the deployment system. This study uses the calculated value based on the allocated MTBF to the system as the demand rate, which is used as input data for the model. Also, we would like to examine changes in inventory level and cost according to the changes in target operational availability and MTBF allocation.