• International conference on construction engineering and project management
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• 2022.06a
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• pp.408-417
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• 2022

Although traditionally perceived as being a visualization and asset management resource, the relatively rapid rate of improvement of computing power, coupled with the proliferation of cloud and edge computing and the IoT has seen the expanded functionality of modern Digital Twins (DTs). These technologies, when applied to buildings, are now providing users with the ability to analyse and predict their energy consumption, implement building controls and identify faults quickly and efficiently, while preserving acceptable comfort and well-being levels. Furthermore, when these building DTs are linked together to form a community DT, entirely new and novel energy management techniques, such as demand side management, demand response, flexibility and local energy markets can be unlocked and analysed in detail, creating circularity in the economy and making ordinary building occupants active participants in the energy market. Through the EU Horizon 2020 funded TwinERGY project, three different levels of DT (consumer - building - community) are being created to support the creation of local energy markets while optimising building performance for real-time occupant preferences and requirements for their building and community. The aim of this research work is to demonstrate the development of this new, interrelated, multi-level DT that can be used as a decision-making tool, helping to determine optimal scenarios simultaneously at consumer, building and community level, while enhancing and successfully supporting the community's management plan implementation.

• Management Science and Financial Engineering
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• v.19 no.1
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• pp.1-10
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• 2013

Hierarchical forecasting strategy does not always outperform direct forecasting strategy. The performance generally depends on demand features. This research guides the use of the alternative forecasting strategies according to demand features. This paper developed and evaluated various classification models such as logistic regression (LR), artificial neural networks (ANN), decision trees (DT), boosted trees (BT), and random forests (RF) for predicting the relative performance of the alternative forecasting strategies for the South Korean navy's spare parts demand which has non-normal characteristics. ANN minimized classification errors and inventory costs, whereas LR minimized the Brier scores and the sum of forecasting errors.

• Management Science and Financial Engineering
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• v.7 no.1
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• pp.1-26
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• 2001

Assume a company sells two products (a and B) in a retail market. the company adopts a specific promotion mechanism, Tie-in Promotion, in which product A's promotional discount coupon is distributed whenever a consumer purchases product B. Product A will later e sold at a markdown price when consumers eventually take the opportunity to redeem the coupon. in the integrated tie-in promotion and stocking policy, we assume managers of two products coordinate by sharing information on the demand forecast and deciding the order quantities and tie-in promotion program to maximize joint profits. The optimal integrated tie-in policy is analyzed. The integrated tie-in promotion model is then compared with two other base models: (1) a decentralized Newsboy model in which no promotion is considered, and (2) an individual promotion model in which managers design a promotion program to promote one of the two products directly. The factors that make an integrated tie-in promotion a better approach are studied.

• Journal of the military operations research society of Korea
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• v.31 no.1
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• pp.73-92
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• 2005

The SCOR(supply chain operations reference) model which is a management tool, has been developed to describe the business activities associated with all phases of satisfying a customer's demand. The model is able to successfully describe and provide a basis for supply chain improvement. In this paper, we review the SCOR model, the present status of the Korean defense logistics system, and suggest an application of the model for the integrated defense logistics system.

• IE interfaces
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• v.16 no.3
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• pp.280-290
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• 2003

Many firms are trying to optimize their production and distribution functions separately, but possible savings by this approach may be limited. Nowadays, it is more important to analyze these two functions simultaneously by trading off the costs associated with the whole. In this paper, I treat a production and distribution planning problem for single-period inventory products comprised of a single production facility and multiple customers, with the aim of optimally coordinating important and interrelated decisions of production sequencing and vehicle routing. Then, I propose a hybrid genetic algorithm incorporating several local optimization techniques, HGAP, for integrated production-distribution planning. Computational results on test problems show that HGAP is effective and generates substantial cost savings over Hurter and Buer's decoupled planning approach in which vehicle routing is first developed and a production sequence is consequently derived. Especially, HGAP performs better on the problems where customers are dispersed with multi-item demand than on the problems where customers are divided into several zones based on single-item demand.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.937-944
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• 2022

Electric vehicles (EVs) have been growing to reduce energy consumption and greenhouse gas (GHG) emissions in the transportation sector. The increasing number of EVs requires adequate recharging infrastructure, and at the same time, adopts low- or zero-emission electricity production because the GHG emissions are highly dependent on primary sources of electricity production. Although previous research has studied solar photovoltaic (PV) -integrated EV charging stations, it is challenging to optimize spatial areas between where the charging stations are required and where the renewable energy sources (i.e., solar photovoltaic (PV)) are accessible. Therefore, the primary objective of this research is to support decisions of siting EV charging stations using a spatial data clustering method integrated with Geographic Information System (GIS). This research explores spatial relationships of PV power outputs (i.e., supply) and traffic flow (i.e., demand) and tests a community in the state of Indiana, USA for optimal sitting of EV charging stations. Under the assumption that EV charging stations should be placed where the potential electricity production and traffic flow are high to match supply and demand, this research identified three areas for installing EV charging stations powered by rooftop PV in the study area. The proposed strategies will drive the transition of existing energy infrastructure into decentralized power systems. This research will ultimately contribute to enhancing economic efficiency and environmental sustainability by enabling significant reductions in electricity distribution loss and GHG emissions driven by transportation energy.

• Journal of Sensor Science and Technology
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• v.32 no.6
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• pp.357-369
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• 2023

Wound healing is a complex and dynamic process, making the accurate and timely assessment of skin wounds a crucial aspect of effective wound care management, especially for chronic wounds. Unlike conventional wound dressings that simply cover the wound area once some form of medicine is administered onto the wound, recent studies have introduced versatile approaches to smart wound dressings capable of interacting with wound fluids to monitor physicochemical and pathological parameters to determine the wound healing status. Such electrochemical wound dressings can be integrated with on-demand, closed-loop drug delivery or stimulation systems and ultimately expanded into an ideal technological platform for the prevention, treatment, and management of skin wounds or illnesses. This article briefly reviews the wound healing mechanism and recent strategies for effective wound care management. Specifically, this review discusses the following aspects of smart wound dressings: sensor-integrated smart bandages to detect wound biomarkers, smart bandages developed to accelerate wound healing, and wireless, closed-loop automatic (on-demand) wound healing systems. This review concludes by providing future perspectives on effective wound care management.

• Journal of The Korean Society of Agricultural Engineers
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• v.65 no.2
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• pp.13-20
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• 2023

In the past, the Ministry of Agriculture, Food, and Rural Affairs (MAFRA) conducted research into and production of agricultural statistics. As a result of organizational changes, these responsibilities were transferred to Statistics Korea in 1998 and 2008. So, the MAFRA managed data without a formal system for managing data and statistical information. The demand for a foundation to improve the usefulness of agri-food statistics has recently increased due to the necessity for basic data representing the realities of rural and agricultural areas. This is especially true for field-oriented agricultural administration. This study aims to propose a strategy for the systematically integrated administration of dispersed data and statistical information. It served as the foundation for the integrated management of distributed administrative and statistical data.

• 한국디지털정책학회:학술대회논문집
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• 2007.06a
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• pp.349-357
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• 2007

We consider supply chain which consist of one manufacturer, one distributor and N retailers for a single product. This paper determines inventory replenishment period of supply chain using houristic method and propose order policy through re-coordination of inventory replenishment. Also, We develops inventory management model to calculate total cost of supply chain under assumptions of constant demand. The computational results show that the proposed inventory replenishment period and inventory management model is efficient.

• Journal of Digital Convergence
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• v.5 no.1
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• pp.47-53
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• 2007

We consider supply chain which consist of one manufacturer, one distributor and N retailers for a single product. This paper determines inventory replenishment period of supply chain using heuristic method and propose order policy through re-coordination of inventory replenishment. Also, We develops inventory management model to calculate total cost of supply chain under assumptions of constant demand. The computational results show that the proposed inventory replenishment period and inventory management model is efficient.