• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.11a
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• pp.142-146
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• 2006

This paper considers a SCM issue concerned with an integrated problem of inventory control and dynamic pricing strategies when demands are price and time dependent. The associated price markdowns are conducted for inventory control in a two-layer market consisting of retailer and outlet as in fashion apparel market. The objective function consists of revenue terms (sales revenue and salvage value) and purchasing cost term. Specifically, decisions on price markdowns and order quantity are made to maximize total profit in the supply chain so as to have zero inventory level at the end of the sales horizon. To solve the proposed problem, a gradient method is applied, which shows an optimal decision on both the initial inventory level and the discount pricing policy. Sensitivity analysis is conducted on the demand parameters and the final comments on the practical use of the proposed model are presented.

• Journal of the Korea Safety Management & Science
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• v.3 no.3
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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.

• Industrial Engineering and Management Systems
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• v.15 no.4
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• pp.354-363
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• 2016

Due to uncertain environment, various parameters such as price, queuing length, warranty, and so on influence on inventory models. In this paper, an inventory-queuing-pricing problem with continuous review inventory control policy and batch arrival queuing approach, is presented. To best of our knowledge, (I) demand function is stochastic and price dependent; (II) due to the uncertainty in real-world situations, a fuzzy programming approach is applied. Therefore, the presented model with goal of maximizing total profit of system analyzes the price and order quantity decision variables. Since the proposed model belongs to NP-hard problems, Pareto-based approaches based on non-dominated ranking and sorting genetic algorithm are proposed and justified to solve the model. Several numerical illustrations are generated to demonstrate the model validity and algorithms performance. The results showed the applicability and robustness of the proposed soft-computing-based approaches to analyze the problem.

• Journal of Korean Institute of Industrial Engineers
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• v.40 no.1
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• pp.108-117
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• 2014

This study considers warehouse sizing decisions in an integrated single vendor-single buyer production inventory system by incorporating new decision variables and constraints associated with warehouse size into the formulations. Two typical inventory control policies proposed in the literature (i.e., Identical Delivery Quantity and Deliver What is Produced) have been investigated with consideration of warehouse investment costs. The numerical study shows that Deliver What is Produced is less flexible than Identical Delivery Quantity, resulting in the conclusion that the latter would be preferable when considering warehouse investment costs.

• Journal of Korean Institute of Industrial Engineers
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• v.37 no.3
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• pp.216-228
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• 2011

A logistics system involving a supplier who produces and delivers a single product and a buyer who receives and sells the product to the final customers is analyzed. In this system, the supplier and the buyer establish a contract which specifies that the supplier will deliver necessary amount of the product to raise inventory up to a specified position at the beginning of each period. A new periodic order-up-to-level inventory control policy specifically designed for nonstationary end customer's demand is proposed for the system. Simulations are used to test the efficiency of the proposed policy. An analysis of the test results reveals that the proposed policy performs much better than does the existing order-up-to-level policy, especially when the demand is nonstationary.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1001-1005
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• 2004

The objective of this paper is to develop the flexible manufacturing system (FMS), which is cooperated with the automatic warehouse and inventory control under holonic manufacturing system (HMS). The HMS is a next wave of manufacturing revolution to deal with dynamic changing. The architecture of HMS is developed for cooperation system between the automatic warehouse agents and the manufacturing agents. This research applies the concept of HMS to develop a distributed control system for automatic warehouse and FMS by industrial network. The parts of prototype manufacturing agents consist of the conveyer system and 3-axises robot that provide the variety patterns in order to work as punch process. Each order of productions depends on the reorder points(RP) of inventory levels. The computation results indicate an improvement by comparing with traditional centralized control.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.05a
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• pp.904-913
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• 2005

This paper deals with an integrated problem of inventory control and dynamic pricing strategies for a commodity with price and sales-period dependent demand pattern, where a seller and customers have complete information of each other. The problem consists of two parts; one is each buyer's benefit problem which makes the best decision on price and time for buyer to purchase items, and the other one is a seller's profit problem which decides an optimal sales strategy concerned with inventory control and discount schedule. The seller's profit function consists of sales revenue and inventory holding cost functions. The two parts are closely related into each other with some related variables, so that any existing general solution methods can not be applied. Therefore, a simplified model with single seller and two customers in considered first, where demand for multiple units is allowed to each customer within a time limit. Therewith, the model is generalized for a n-customer-classes problem. To solve the proposed n-customer-set problem, a dynamic programming algorithm is derived. In the proposed dynamic programming algorithm, an intermediate profit function is used, which is computed in case of a fixed initial inventory level and then adjusted in searching for an optimal inventory level. This leads to an optimal sales strategy for a seller, which can derive an optimal decision on both an initial inventory level and a discount schedule, in $O(n^2)$ time. This result can be used for some extended problems with a small customer set and a short selling period, including sales strategy for department stores, Dutch auction for items with heavy holding cost, open tender of materials, quantity-limited sales, and cooperative buying in the on/off markets.

• IE interfaces
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• v.10 no.1
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• pp.119-134
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• 1997

The management of blood inventory is very important within the medical care system. The efficient management of blood supplies and demands for transfusions is of great economic and social importance to both hospitals and patients. For any blood type, there is a complex interaction among the optimal inventory level, daily demand level, daily supply level, transfusion to crossmatch ratio, crossmatch release period, issuing policy and the age of arriving units that determine the shortage and outdate rate. In this paper, we develop an efficient decision rule for blood inventory management in a hospital blood bank which can support efficient hospital blood inventory management using simulation. The primary use of the efficient decision rule will be to establish minimum cost function which consists of inventory levels, period in inventory, outdate and shortage rate for whole blood and various component inventories for a hospital blood bank or a transfusion service. If the administrator compute the mean daily demand for each blood type, the mean daily supply for each blood type, the length of the crossmatch release period and the average transfusion to crossmatch ratio, then it is possible to apply the efficient decision rule to compute the optimal inventory level, inventory period, outdate and shortage rate. This rule can also be used as a decision support system that allows the blood bank administrator to do sensitivity analysis related to controllable blood inventory parameters.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.3
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• pp.61-67
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• 2020

The fourth industrial revolution encourages manufacturing industry to pursue a new paradigm shift to meet customers' diverse demands by managing the production process efficiently. However, it is not easy to manage efficiently a variety of tasks of all the processes including materials management, production management, process control, sales management, and inventory management. Especially, to set up an efficient production schedule and maintain appropriate inventory is crucial for tailored response to customers' needs. This paper deals with the optimized inventory policy in a steel company that produces granule products under supply contracts of three targeted on-time delivery rates. For efficient inventory management, products are classified into three groups A, B and C, and three differentiated production cycles and safety factors are assumed for the targeted on-time delivery rates of the groups. To derive the optimized inventory policy, we experimented eight cases of combined safety stock and data analysis methods in terms of key performance metrics such as mean inventory level and sold-out rate. Through simulation experiments based on real data we find that the proposed optimized inventory policy reduces inventory level by about 9%, and increases surplus production capacity rate, which is usually used for the production of products in Group C, from 43.4% to 46.3%, compared with the existing inventory policy.

• Journal of the Korea Safety Management & Science
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• v.16 no.4
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• pp.323-330
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• 2014

Various inventory control theories have tried to modelling and analyzing supply chains by using quantitative methods and characterization of optimal control policies. However, despite of various efforts in this research filed, the existing models cannot afford to be applied to the realistic problems. The most unrealistic assumption for these models is customer demand. Most of previous researches assume that the customer demand is stationary with a known distribution, whereas, in reality, the customer demand is not known a priori and changes over time. In this paper, we propose a reinforcement learning based adaptive echelon base-stock inventory control policy for a multi-stage, serial supply chain with non-stationary customer demand under the service level constraint. Using various simulation experiments, we prove that the proposed inventory control policy can meet the target service level quite well under various experimental environments.