• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.11a
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• pp.506-512
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• 2006

In this paper, we propose a lot-sizing and scheduling problem that seeks to minimize the sum of production cost and inventory cost over a given planning horizon while considering idle state of a machine in a batch production system. For this problem, we develop an integer programming model. And, we develop an efficient 2-phase heuristic algorithm to find a high quality feasible solution within reasonable time bounds. In the first phase, we seek to minimize the production cost by assigning batches to machines. Then, in the second phase, we find a production sequence of batches that reduces the inventory cost, while considering adding or deleting idle states between batches. Computational results show that the developed heuristic algorithm finds excellent feasible solutions within reasonable time bounds. Also, we could significantly reduce the total cost consisting of production cost and inventory cost by using the developed heuristic algorithm at a real manufacturing system that produces zinc alloys.

• Journal of the Korean Operations Research and Management Science Society
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• v.17 no.3
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• pp.27-46
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• 1992

This paper considers an (r, Q) policy for operation of a multipurpose facility. It is assumed that whenever the inventory level falls below r, the model starts to produce the fixed amount of Q. The facility can be utilized for extra production during idle periods, that is, when the inventory level is still greater than r right after a main production operation is terminated or an extra production operation is finished. But, whenever the facility is in operation for an extra production, the operation can not be terminated for the main production even though the inventory level falls below r. In the model, the demand for the product is assumed to arrive according to a compound Poisson process and the processing time required to produce a product is assumed to follow an arbitary distribution. Similarly, the orders for the extra production is assumed to accur in a Poisson process are the extra production processing time is assumed to follow an arbitrary distribution. It is further assumed that unsatisfied demands are backordered and the expected comulative amount of demands is less than that of production during each production period. Under a cost structure which includes a setup/ production cost, a linear holding cost, a linear backorder cost, a linear extra production lost sale cost, and a linear extra production profit, an expression for the expected cost per unit time for a given (r, Q) policy is obtained, and using a convex property of the cost function, a procedure to find the optimal (r, Q) policy is presented.

• Journal of Distribution Science
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• v.19 no.11
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• pp.59-68
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• 2021

Purpose: The Covid-19 pandemic has had excessively severe impacts on all the nodes and edges of any supply chain due to changes in consumer behaviours and lockdown restrictions from governments among countries. This article aims to provide a simulating experiment on how a supply chain deals with supply disruption risks by flexibility in the inventory level of each sector as a buffer considering the overall cost to fulfil demand in the market. Research design, data and methodology: Agent-based simulation techniques are used to determine the cost-efficiency and customer waiting time related to varying inventory levels of each member in the supply chain when using inventory buffers. Findings: This study has shown that any sudden changes in the inventory level of each sector are likely to impact the rest of the supply chain. Among all sectors, the wholesaler will be impacted more severely than others. Also, the manufacturing sector is the most suitable node to adjust inventory depending on its manufacturing ability. Conclusion: The findings of the study provide insightful implications for decision-makers to adjust inventory levels and policymakers to maintain manufacturing activities in the context of the pandemic restrictions to deal with the excessive demand and potential supply disruption risks.

• The Journal of the Convergence on Culture Technology
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• v.5 no.1
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• pp.353-360
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• 2019

Trade credit is being used as a price discrimination strategy by the suppliers in order to increase the customer's demand. From the viewpoint of the customer, if delayed payment is allowed for a certain period of time from the supplier, the effect of reducing the inventory carrying cost will positively affect the customer's order quantity. Also, in deriving the economic order quantity(EOQ) formula, it is tacitly assumed that the customer's ordering cost is a fixed cost. However in many business transactions, the customer pays the freight cost for the transportation of his order and so, the customer's ordering cost contains not only a fixed cost but also a freight cost which is a function of the order size. Therefore, in this study, we analyzed the inventory model which considers that the customer's ordering cost contains not only a fixed cost but also a freight cost which is a function of the customer's order size when the supplier permits a delay in payments. For the analysis, it is also assumed that inventory is exhausted not only by customer's demand but also by deterioration. Investigation of the properties of an optimal solution allows us to develop an algorithm whose validity is illustrated using an example problem.

• Journal of the Korean Operations Research and Management Science Society
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• v.6 no.2
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• pp.51-55
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• 1981

In both continuous-review and periodic-review non-stationary inventory systems, the non-stationary Poisson demand process and the associated inventory position processes were proved being mutually independent of each other, which lead to the probability distribution of the corresponding net inventory position process in the form of a finite product sum of those two process distributions. It is also discussed how these results can correspond to analytical stochastic inventory cost function formulations in terms of the probability distributions of the processes.

• Journal of the Korean Operations Research and Management Science Society
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• v.24 no.3
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• pp.1-11
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• 1999

We consider the problem of determining the spare inventory level for a multiechelon repairable-item inventory system. Our model extends the previous results to the system which has an inventory at the central depot as well as bases. We develop an optimal algorithm to find spare inventory leveis, which minimize the total expected cost and simultaneously satisfy a specified minimum service rate. The algorithm is tested using problems of various sizes to verify the efficiency and accuracy.

• Journal of the Korean Operations Research and Management Science Society
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• v.19 no.1
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• pp.169-187
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• 1994

The efficiency of marketing channel of distribution between a sholesaler and a retailer with uncertain characteristics can be improved by influencing the retailer's ordering pattern. The wholesaler with large unit invetory holding cost can offer a large quantity discount tanks to the great benefit which comes from the transfer of part of his inventory to retailer. The retailer's increasing average inventory holding cost can be offset by the quantity discount and by savings of the ordering cost. Conditions under which marketing channel improvement can be possible are derived.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.18 no.35
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• pp.131-138
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• 1995

For the purpose of the reduction of tile cost, a production/inventory model including the interference phenomenon was developed. By investigating the cause and the characteristics of the direct/indirect cost due to the interference phenomenon, a strategy for suitable production was developed. The developed model was quantitatively validated using an existing-EPQ model and the SIMAN package was used to simulate and animate the model. Consequently, it was presented that the total operating cost of the system could be decreased with tile proposed model.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.30 no.3
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• pp.12-19
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• 2007

This paper is to determine the transportation size and the location of distribution centers to minimize logistics cost in a distribution system where products are transported from the distribution centers to the retailers. Logistics cost consists of the fixed cost of distribution centers, the transportation cost from the distribution centers to the retailers and the inventory holding cost in the retailers. The logistics cost is affected by the transportation size and the location of distribution centers. The transportation size affects transportation cost and inventory holding cost. The location of distribution centers affects the transportation cost. A mathematical model is formulated and the algorithm is developed. A numerical example is shown to explain the problem.

• Journal of the Korean Operations Research and Management Science Society
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• v.1 no.1
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• pp.151-170
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• 1976

There are many cases of production processes which intermittently produce several different kinds of products for stock through one set of physical facility. In this case, an important question is what size of production run should be prduced once we do set-up for a product in order to minimize the total cost, that is, the sum of the set-up, carrying, and stock-out costs. This problem is used to be called scheduling of multiple products through a single facility in the production management field. Despite the very common occurrence of this type of production process, no one has yet devised a method for determining the optimal production schedule. The purpose of this study is to develop quantitative analytical models which can be used practically and give us rational production schedules. The study is to show improved models with application to a can-manufacturing plant. In this thesis the economic production quantity (EPQ) model was used as a basic model to develop quantitative analytical models for this scheduling problem and two cases, one with stock-out cost, the other without stock-out cost, were taken into consideration. The first analytical model was developed for the scheduling of products through a single facility. In this model we calculate No, the optimal number of production runs per year, minimizing the total annual cost above all. Next we calculate No$_{i}$ is significantly different from No, some manipulation of the schedule can be made by trial and error in order to try to fit the product into the basic (No schedule either more or less frequently as dictated by) No$_{i}$, But this trial and error schedule is thought of inefficient. The second analytical model was developed by reinterpretation by reinterpretation of the calculating process of the economic production quantity model. In this model we obtained two relationships, one of which is the relationship between optimal number of set-ups for the ith item and optimal total number of set-ups, the other is the relationship between optimal average inventory investment for the ith item and optimal total average inventory investment. From these relationships we can determine how much average inventory investment per year would be required if a rational policy based on m No set-ups per year for m products were followed and, alternatively, how many set-ups per year would be required if a rational policy were followed which required an established total average inventory inventory investment. We also learned the relationship between the number of set-ups and the average inventory investment takes the form of a hyperbola. But, there is no reason to say that the first analytical model is superior to the second analytical model. It can be said that the first model is useful for a basic production schedule. On the other hand, the second model is efficient to get an improved production schedule, in a sense of reducing the total cost. Another merit of the second model is that, unlike the first model where we have to know all the inventory costs for each product, we can obtain an improved production schedule with unknown inventory costs. The application of these quantitative analytical models to PoHang can-manufacturing plants shows this point.int.