• Proceedings of the Korean Operations and Management Science Society Conference
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• 2002.05a
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• pp.463-468
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• 2002

Recently, a multi-facility, multi-product and multi-period industrial problem has been widely investigated in Supply Chain Management(SCM). One of the key issues in the current SCM research area involves reducing both production and distribution costs. We have developed an optimization model to tackle the above problems under the restricted conditions such as transportation time and a zero inventory. The model can be used to deride an appropriate factory and assign an optimal output the factory yields. This paper deals with the main idea of the proposed methodology in depth.

• Journal of the Korea Safety Management & Science
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• v.10 no.1
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• pp.139-144
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• 2008

Recently, a multi-facility, multi-product and multi-period industrial production-distribution planning problem has been widely investigated in Supply Chain Management (SCM). One of the key issues in the current SCM research area involves reducing both production and distribution costs. We have developed an optimization model to tackle the above problems under the restricted conditions such as transportation time and a zero inventory. Computational experiments using commercial tool Ms-Excel Solver show that the real size problems we encountered can be solved in reasonable time. The model can be used to decide an appropriate production-distribution planning problem in SCM research area.

• Journal of the Korea Society for Simulation
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• v.14 no.3
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• pp.67-77
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• 2005

Logistics network of the enterprise is defined to determine the optimal node and link considering the production, inventory and transportation based on the demand forecasting. This study consider the optimal logistics network of A painter company which maintain the existing transportation network and plan to relocate its plants and build new distribution centers. For this, we design possible alternative scenarios and install the simulation models for analysis of each scenario. The result of simulation will help the proper logistic network and determining the size of distribution center further.

• Journal of Korean Institute of Industrial Engineers
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• v.41 no.5
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• pp.511-520
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• 2015

Inventory, cost, and the level of service are three interrelated key metrics that most supply chain organizations are striving to optimize. One way to achieve this goal is to create a simulation model to conduct sensitivity analysis and optimization on several different supply chain policies that can be implemented in actual operation. In this paper, a case of Xerox global supply chain modeling and analysis to assess several "what if" scenarios for the consumable policy safety stock is presented. The simulation model, combined with analytical cost model and optimization module, is used to optimize the policy safety stock level to achieve the lowest total value chain cost. It was shown quantitatively that the policy safety stock can be reduced, but it is offset by the inbound premium transportation cost to expedite supplies in shortage, and the outbound premium transportation cost to send supplies to customers via express shipment, requiring fine balance.

• Journal of Korean Society of Transportation
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• v.15 no.1
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• pp.63-83
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• 1997

수송비와 재고관리비는 총 물류비용의 50% 이상을 차지할 정도로 그 중요성이 크 며, 이들 두 요소는 상호 정밀하게 관련되어 있어서 비용 트레이드 오프 관계가 존재한다. 이러한 관점에서 제품을 수송하는데 소요되는 총비용을 도출하고 비용이 최소가 되는 수송 수단을 선택할 수 있다. 이같은 분석은 수요와 리드타임이 불확실한 경우 수송시간, 고객 서비스 수준, 안전재고 수준, 주문량, 물류비용 등의 관계가 복잡해지기 때문에 해를 구하는 과정이 복잡하게 된다. 따라서 리드타임 동안의 수요를 나타내는 방법과 수송 시간의 신뢰 도와 관련된 안전재고 측정 및 기준에 대한 다양한 방법이 재고이론에 근거한 화물수송수단 선택모형 연구의 주 관심사가 된다. 본 연구는 국외에서 발표된 관련 연구들을 중심으로 재 고와 수송의 상관관계에 대하여 이론적으로 고찰하여 연구 현황을 밝히고 앞으로의 연구 방 향을 제시함으로써 이 분야의 이론적인 발전에 기여하는 것을 목적으로 한다. 연구의 주안 점은 확률적 리드타임과 수요에 대한 연구에서 쟁점이 되는 리드 타임 동안의 수요를 나타 내는 방법과 안전재고를 결정하는 기준에 모아진다.

• Journal of Climate Change Research
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• v.7 no.3
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• pp.289-297
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• 2016

In this study, we researched the emission source category and it was calculated emissions estimates from existing research or literature review related to port. In addition, we have created the basis for a policy that can reduce greenhouse gas emissions calculation based on the results of the harbor. Greenhouse gas emissions estimation results, we proposed a method for allocating the GIS space. In this study, we confirmed based on the calculated greenhouse gas emissions by sources resulting in the GIS Map Port result of the expression construct for space allocation. Based on these results, it tries to provide the basic data that can be used when you want to create a local government measures to reduce scenario in the future.

• International Journal of Computer Science & Network Security
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• v.21 no.7
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• pp.87-92
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• 2021

Analysis of current state of construction industry functioning in Ukraine allows us to identify a number of problems having negative impact on sustainable development of construction industry, especially in terms of its organization. Therefore, it is absolutely essential to study existing methods of organization system supplying construction sites with necessary material resources. Companies can develop their own logistics departments, which independently solve logistics issues related to transportation organization and management, accounting and inventory management, acquisition and warehousing, intercommunication (ability to obtain both final and intermediate information during transporting materials). Using a complex of methods is substantiated: the hierarchy analysis method (Saati's method), the network method, the defect elimination algorithm DEA, the transportation problem that finds optimal problem solutions for construction sector with the purpose of rational supplying uninterrupted construction with building resources in the designed model "provider-transportation-costs".

• Korean Journal of Artificial Intelligence
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• v.10 no.1
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• pp.27-32
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• 2022

As the need for eco-friendly transportation increases due to the deepening climate crisis, many local governments in Korea are introducing shared bicycles. Due to anxiety about public transportation after COVID-19, bicycles have firmly established themselves as the axis of daily transportation. The use of shared bicycles is spread, and the demand for bicycles is increasing by rental offices, but there are operational and management difficulties because the demand is managed under a limited budget. And unfortunately, user behavior results in a spatial imbalance of the bike inventory over time. So, in order to easily operate the maintenance of shared bicycles in Seoul, bicycles should be prepared in large quantities at a time of high demand and withdrawn at a low time. Therefore, in this study, by using machine learning, the linear regression algorithm and MS Azure ML are used to predict and analyze when demand is high. As a result of the analysis, the demand for bicycles in 2018 is on the rise compared to 2017, and the demand is lower in winter than in spring, summer, and fall. It can be judged that this linear regression-based prediction can reduce maintenance and management costs in a shared society and increase user convenience. In a further study, we will focus on shared bike routes by using GPS tracking systems. Through the data found, the route used by most people will be analyzed to derive the optimal route when installing a bicycle-only road.

• Journal of Distribution Science
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• v.7 no.4
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• pp.47-56
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• 2009

The purpose of this study is to present an alternative improving the efficient and reasonable of the physical distribution system management is influenced by many factors. Therefore, the study depends on the documentary method and survey method to achieve the purpose of this study. The major components of a physical distribution system are refers to as elements, include warehouse·storage system, transportation system, inventory system, physical distribution information system. The factors used in this study are ① factor of product(quality·A/S·added value of product·adaption of product·technical competitive power to other enterprises), ② factor of market(market channel·kinds of customer·physical distribution share), ③ factor of warehouse·storage(warehouse design·size·direction·storage ability·warehouse quality), ④ factor of transportation(promptness·reliability·responsibility·kinds of transportation·cooperation united transportation system·national transportation network), ⑤ factor of packaging (packaging design·material·educating program·pollution degree measure program), ⑥ factor of inventory(ordinary inventory criterion·consistence for inventories record), ⑦ factor of unloaded(unloaded machine·having machine ratio), ⑧ factor of information system (physical distribution quantity analysis·usable computer part), ⑨ factor of physical distribution cost(sales ratio to product) ⑩ factor of physical distribution system(physical distribution center etc). The implication of this study can be summarized as follows: ① In firms that have not adopted a systems integrative approach, physical distribution is a fragmented and often uncoordinated set of activities spread throughout various functions with function having its own set of priorities and measurements. ② The physical distribution is recognized as more an important strategic factor than a simple cost reduction factor, ③ It can be used a strategic competition tool to enterprise.

• Asian Journal of Atmospheric Environment
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• v.5 no.1
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• pp.41-46
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• 2011

The port of Busan is the fifth busiest container port in the world in terms of total mass of 20-foot equivalent units transported. Yet no attempts have been made to estimate the greenhouse gas (GHG) emissions from the port of Busan by accounting for all port-related activities of the various transportation modes. With these challenges in mind, this study estimates the first activity-based GHG emissions inventory in the port of Busan, which consists of four transportation modes: marine vessels, cargo-handling equipment, heavy-duty trucks, and railroad locomotives. The estimation results based on the most recent and complete port-related activity data are as follows. First, the average annual transportation GHG emission in the port of Busan during the analysis period from 2000 to 2007 was 802 Gg $CO_2$-eq, with a lower value of 773 Gg $CO_2$-eq and an upper value of 813 Gg $CO_2$-eq. Second, the increase in the transportation-related GHG emissions in the port of Busan during the analysis period can be systematically explained by the amount of cargo handled ($R^2$=0.98). Third, about 64% of total GHG emissions in the port of Busan were from marine vessels because more than 40% of all maritime containerized trade flows in the port were transshipment traffic. Fourth, approximately 22% of the total GHG emissions in the port of Busan were from on-road or railroad vehicles, which transport cargo to and from the port of Busan. Finally, the remaining 14% of total GHG emissions were from the cargo handling equipment, such as cranes, yard tractors, and reach stackers.