• Title/Summary/Keyword: inventory method

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A Study on an Inventory Model for Fish Culture Items with Weibull Ameliorating (증식률을 고려한 양식어류의 적정 물류재고모델의 연구)

  • 황흥석
    • The Journal of Fisheries Business Administration
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    • v.27 no.1
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    • pp.57-65
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    • 1996
  • This paper is concerned with the development of ameliorating inventory models. The ameliorating inventory is the inventory of goods whose utility increases over the time by ameliorating activation. The term ameliorating inventory is used in this paper at least, since the terminology is not standard well known. This study is performed according to areas; one is an economic order quantity(EOQ) model for the items whose utility is ameliorating in accordance with Weibull distribution, and the other is a partial selling quantity(PSQ) model developed for selling the surplus inventory accumulated by ameliorating activation. The proposed models cannot be solved directly in a closed form, thus we used a computer program and a graphical solution method to obtain the optimal ordering and setting quantity in this paper. Numerical examples to illustrate the effect of ameliorating rate on inventory polices are shown at the end of this paper.

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Automation of Inventory Checking System for Outdoor Warehouse (야외창고 재고실사 자동화를 위한 시스템 개발)

  • Bae, Sung Moon;Han, Kwan Hee;Lee, Hwa Yong;Hong, Kum Suk
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.41 no.3
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    • pp.138-144
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    • 2018
  • Inventory inspection is an important task to eliminate the inconsistency between real assets and inventory management systems, and it is performed periodically at the site. In the case of a large-sized property, it is mainly managed in an outdoor workshop or a warehouse. However, due to the large area of the outdoor area, it is relatively difficult to identify the quantity and location of the property and is also vulnerable to theft. To solve this problem, we proposed a method and system for performing a warehouse inventory inspection using an unmanned aerial vehicle (UAV) and Bluetooth low energy (BLE) beacons. The proposed method has the following advantages. First of all, if we carry out inventory inspection by utilizing UAV, we can minimize user's effort compared to existing methods. The method of recognizing the asset by attaching the BLE beacon is more costly than using the existing RFID technology, but it is advantageous because the recognition distance is increased and the battery life of the tag is drastically increased. We also designed a BLE beacon reader for the system and implemented a prototype to show the feasibility of the proposed system. The prototype is based on Genuino 101, which is a kind of arduino, and adds HM-10 and Neo-6m modules to provide Bluetooth and GPS functions. The BLE beacon reader was tested in outdoor, and attached in drone. We also developed an inventory checking system based on the web to display results of inventory checking. The proposed approach enables the users to automate the operation of inventory checking on an outdoor warehouse.

인공신경망을 이용한 공급 사슬 상에서의 재고관리

  • 정성원;서용원;박찬권;박진우
    • Proceedings of the Korea Society for Simulation Conference
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    • 2002.11a
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    • pp.101-105
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    • 2002
  • In a traditional hierarchical inventory system, direct orders are the only information for inventory management that is exchanged between the firms involved. But due to the rapid development of modern information technology, it becomes possible for the firms to share more information in real time, e.g. demand and inventory status data. And so the term Supply Chain has emerged because it is seen as an important source of competitive advantage. Now it is possible to challenge traditional approaches to inventory management. In the past, one of the de-facto assumptions for inventory management was that the demand pattern follows a specific distribution function. However, it is undesirable to apply this assumption in real situations because the demand information in the supply chain tends to be distorted due to the bullwhip effect in a supply chain. To overcome this weakness, we propose a new solution method using NN (Neural Network). Our method proceeds in three steps. First, we find the patterns of optimal reorder points by analyzing past data. Second. train the NN using these pattern data and finally decide the reorder point. Using simulation experiment, we show that the proposed solution method gives better result than that of traditional research.

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Study on the Validity of Inventory Sharing System for the Strategic Cooperation of Outsourcing Companies (아웃소싱 업체의 전략적 제휴를 위한 재고 공유 시스템 타당성 연구 - 제조업체 재고 및 판매 중심으로 -)

  • 김경섭;박진원;정석재;송일윤
    • Journal of the Korea Society for Simulation
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    • v.12 no.4
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    • pp.61-71
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    • 2003
  • Recently, a matter of the highest priority that the company must do for the satisfaction of customer service is that the company ensure the competitive power throughout the strategic cooperation in the market environment changing rapidly In this situation, one of allied strategies is the supply chain management and the outsourcing is one of the supply chain management strategies. In this paper, the inventory sharing system is introduced as the method to solve two inconsistency problem such as inventory and customer service. This paper also suggests how to increase customer service and to decrease inventory throughout construction of the inventory sharing system among outsourcing companies. For this, we experimented the effect of the inventory sharing system on the supply chain dynamics by using the simulation modeling and analyzed the validity about construction of the inventory sharing system presented in this study. The simulation is designed by Vensim(Process simulation package) and has some feedback loops.

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Development of Inventory Control System for Large-scale Retailers using Neural Network and (s*,S*) Policy (신경회로망과 (s*,S*) 정책을 이용한 대규모 유통업을 위한 재고 관리 시스템의 개발)

  • 김우주
    • The Journal of Information Systems
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    • v.6 no.1
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    • pp.223-256
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    • 1997
  • Since the business scales of retailing companies become to be very large and the number of items dealt increases explosively, automation of inventory management becomes one of the most important issues to solve in retailing industry. In order to accomplish this automation of inventory management, there must be a great need to a method which can perform real-time decision making on inventory control in an automatic fashion, while communicating with inventory information systems like POS system and automatic warehousing system. But even in this circumstance, there are also many obstructions to such automation like varying demands, limited capacity of warehouse and exhibition room, need for strategic consideration on inventory control, etc., in a real sense. Due to these reasons, it seems very difficult that most large-scaled retailing companies get fully automated inventory management system. To overcome those difficulties and reflect them into inventory control, we propose a automated inventory control methodology for retailing industry based on neural network and policy model. Especially, policy model is devised to deal with dynamic varying demands and using this model, strategic goals on inventory can be considered into inventory control mechanism. Our proposed approach is implemented in workstation and its performance is also empirically verified also against to real case of one of the major retailing firm in Korea.

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An Inventory Problem with Lead Time Proportional to Lot Size and Space Constraint (로트크기에 비례하는 리드타임과 공간 제약을 고려한 재고관리 정책)

  • Lee, Dongju
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.38 no.4
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    • pp.109-116
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    • 2015
  • This paper is concerned with the single vendor single buyer integrated production inventory problem. To make this problem more practical, space restriction and lead time proportional to lot size are considered. Since the space for the inventory is limited in most practical inventory system, the space restriction for the inventory of a vendor and a buyer is considered. As product's quantity to be manufactured by the vendor is increased, the lead time for the order is usually increased. Therefore, lead time for the product is proportional to the order quantity by the buyer. Demand is assumed to be stochastic and the continuous review inventory policy is used by the buyer. If the buyer places an order, then the vendor will start to manufacture products and the products will be transferred to the buyer with equal shipments many times. The mathematical formulation with space restriction for the inventory of a vendor and a buyer is suggested in this paper. This problem is constrained nonlinear integer programming problem. Order quantity, reorder points for the buyer, and the number of shipments are required to be determined. A Lagrangian relaxation approach, a popular solution method for constrained problem, is developed to find lower bound of this problem. Since a Lagrangian relaxation approach cannot guarantee the feasible solution, the solution method based on the Lagrangian relaxation approach is proposed to provide with a good feasible solution. Total costs by the proposed method are pretty close to those by the Lagrangian relaxation approach. Sensitivity analysis for space restriction for the vendor and the buyer is done to figure out the relationships between parameters.

Endosymbiotic Evolutionary Algorithm for the Combined Location Routing and Inventory Problem with Budget Constrained (초기투자비 제약을 고려한 입지..경로..재고문제의 내공생진화 알고리듬 해법)

  • Song, Seok-Hyun;Lee, Sang-Heon
    • Journal of Korean Institute of Industrial Engineers
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    • v.37 no.1
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    • pp.1-9
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    • 2011
  • This paper presents a new method that can solve the integrated problem of combined location routing and inventory problem (CLRIP) efficiently. The CLRIP is used to establish facilities from several candidate depots, to find the optimal set of vehicle routes, and to determine the inventory policy in order to minimize the total system cost. We propose a mathematical model for the CLRIP with budget constrained. Because this model is a nonpolynomial (NP) problem, we propose a endosymbiotic evolutionary algorithm (EEA) which is a kind of symbiotic evolutionary algorithm (SEA). The heuristic method is used to obtaining the initial solutions for the EEA. The experimental results show that EEA perform very well compared to the existing heuristic methods with considering inventory control decisions.

An Adaptive Vendor Managed Inventory Model Using Action-Reward Learning Method (행동-보상 학습 기법을 이용한 적응형 VMI 모형)

  • Kim Chang-Ouk;Baek Jun-Geol;Choi Jin-Sung;Kwon Ick-Hyun
    • Journal of the Korean Operations Research and Management Science Society
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    • v.31 no.3
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    • pp.27-40
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    • 2006
  • Today's customer demands in supply chains tend to change quickly, variously even in a short time Interval. The uncertainties of customer demands make it difficult for supply chains to achieve efficient inventory replenishment, resulting in loosing sales opportunity or keeping excessive chain wide inventories. Un this paper, we propose an adaptive vendor managed inventory (VMI) model for a two-echelon supply chain with non-stationary customer demands using the action-reward learning method. The Purpose of this model is to decrease the inventory cost adaptively. The control Parameter, a compensation factor, is designed to adaptively change as customer demand pattern changes. A simulation-based experiment was performed to compare the performance of the adaptive VMI model.

A Simulation Study on a Variant Policy of Inventory Replenishment for the Order Consolidation - A Case of Steel Industry (주문 집약을 위한 재고 변용 모델 연구: 제철산업의 소로트 주문 집약 활용을 중심으로)

  • Jung, Jae-Heon
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 2005.10a
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    • pp.10-26
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    • 2005
  • In our model, we keep inventory to satisfy uncertain demands which arrives irregularly. In this situation, we have additional two constraints. First, we need to have certain amount of order consolidation (consolidation constraint) for the orders to replenish the inventory because of production or purchase constraint. And also, if we order at a certain date which was set by administrative convenience, we have amount constraint to order the consolidated order demands (capacity constraint). We showed this variant inventory policy is needed in steel industry and note that there will be possible similar case in industry. To deal with this case, we invented a variant replenishment policy and show this policy is superior to other possible polices in the consolidation constraint case by extensive simulation. And we derive a combined solution method for dealing with the capacity constraints in addition to the consolidation constraints. For this, we suggest a combined solution method of integer programming and simulation.

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A Simulation Study on a Variant Policy of Inventory Replenishment for the Order Consolidation : A Case of Steel Industry (주문 집약을 위한 재고 변용 모델 연구 : 제철산업의 소로트 주문 집약 활용을 중심으로)

  • Jung Jae-Heon
    • Journal of the Korean Operations Research and Management Science Society
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    • v.31 no.2
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    • pp.99-112
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    • 2006
  • In our model, we keep inventory to satisfy uncertain demands which arrives irregularly. In this situation, we have additional two constraints. First, we need to have certain amount of order consolidation (consolidation constraint) for the orders to replenish the inventory because of production or purchase amount constraint. And also, if we order at a certain date which was set by administrative convenience, we have capacity constraint to order the consolidated order demands (capacity constraint). We show this variant inventory policy is needed in steel industry and note that there will be possible similar case in industry. To deal with this case, we invent a variant replenishment policy and show this policy is superior to other possible polices in the consolidation constraint case by extensive simulation. And we derive a combined solution method for dealing with the capacity constraints in addition to the consolidation constraints. For this, we suggest a combined solution method of integer programming and simulation.