• IE interfaces
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• v.11 no.1
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• pp.85-95
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• 1998

This study is focussed on an optimal vehicle routing model for multi-supply centers in two-echelon logistic system. The aim of this study is to deliver goods for demand sites with optimal decision. This study investigated an integrated model using step-by-step approach based on relationship that exists between the inventory allocation and vehicle routing with restricted amount of inventory and transportations such as the capability of supply centers, vehicle capacity and transportation parameters. Three sub-models are developed: 1) sector-clustering model, 2) a vehicle-routing model based on clustering and a heuristic algorithm, and 3) a vehicle route scheduling model using TSP-solver based on genetic and branch-and-bound algorithm. Also, we have developed computer programs for each sub-models and user interface with visualization for major inputs and outputs. The application and superior performance of the proposed model are demonstrated by several sample runs for the inventory-allocation and vehicle routing problems.

• Journal of Digital Convergence
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• v.11 no.2
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• pp.175-182
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• 2013

In this paper, the simulation model of house price is presented on the basis of pricing mechanism between the demand and the supply of apartments in seoul. The algorithm of house price simulation model for calculating the rate of price over time includes feedback control theory. The feedback control theory consists of stock variable, flow variable, auxiliary variable and constant variable. We suggest that the future price of apartment is simulated using mutual interaction variables which are demand, supply, price and parameters among them. In this paper we considers three items which include the behavior of apartment price index, the size of demand and supply, and the forecasting of the apartment price in the future economic scenarios. The proposed price simulation model could be used in public needs for developing a house price regulation policy using financial and non-financial aids. And the quantitative simulation model is to be applied in practice with more specific real data and Powersim Software modeling tool.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.9
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• pp.3304-3310
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• 2010

This study solves the decision making problems for TFT-LCD manufacturing supply chain with demand and price uncertainties by establishing robust production and distribution strategies. In order to control the decisions regarding production graded by quality, inventory level and distribution, this study develop scenario model based stochastic mixed integer linear programs (SMILPs) that consider demand and price uncertainties as well as realistic constraints such as capacities etc. The performance of the solution obtained from the SMILPs using robust algorithms will be evaluated through various scenarios.

• Journal of Distribution Science
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• v.20 no.12
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• pp.59-69
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• 2022

Purpose: The purpose of this research is to identify and design a model for the integration between marketing and supply chain management (SCM) of technopreneurship-based souvenirs MSMEs to fulfil customer value creation. Research design, data and methodology: This research method uses the system development life cycle method. This study draws its insights and conclusions from a literature review in several fields followed by an interactive research approach that helps identify, validate, and implement a theoretical framework so that the modelling results can be adopted in applicative manner for souvenir MSMEs. Result: Implementing the "G-ASPOO-L" supply chain management integration model based on technopreneruship to fulfil value creation in the 5.0 society era created three perspectives: an inter-functional perspective, a process perspective, and an integrated business concept perspective. The supply chain management involves enterprise integration, strategic customer integration, strategic supplier integration, and marketing strategy integration. Conclusion: The proposed model framework leads to managerial problems of supply chain management strategy, which urgently requires an interaction approach that challenges the traditional view of demand creation and implementation of supply chain management to fulfil value creation. This research leverages existing knowledge and advances our understanding of the strategic integration issues companies face in digital-based competition.

• Journal of Biosystems Engineering
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• v.31 no.3 s.116
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• pp.194-202
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• 2006

Using a multi-variable linear regression technique and SUR(seemingly unrelated regression) model, the demand functions of tractor, combine and rice transplanter were estimated. The demand was regarded as an annual supply of each machine and modeled as a function of 11 independent variables which reflect the actual farmer's income, actual prices of farm machines, previous supply, previous stock, actual amount of available subsidy, actual amount of available loan, arable land, import of farm machines and rice price. The actual amount of available loan affects most significantly the demand functions. The actual farmer's income, actual farmer's asset, loan coverage, and rice price affect the demand positively while prices of farm machines and import negatively. The annual demands of tractor, combine and rice transplanter estimated using the demand functions were also presented over the next 4 years.

• Health Policy and Management
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• v.32 no.1
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• pp.73-93
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• 2022

Background: Appropriate physician workforce projection through reasonable discussions and decisions with a broad view on supply and demand of the workforce, thus, is very important for high-quality healthcare services. The study expects to provide preliminary research data on the workforce diagnosis standard model for Korean physician workforce policy decision through more flexible and objective physician workforce projection in reflection of diverse changes in healthcare policy and sociodemographic environments. Methods: A low flow rate through the causal map was developed, and an objective workforce demand projection from 2019 to 2040 was conducted. In addition, projections by scenarios under various situations were conducted with the low flow rate developed in the study. Lastly, the demand projection of the physician workforce by region of 17 cities and provinces was conducted. Results: First, demand of physicians in 2019 was 110,665, 113,450 in 2020, 129,496 in 2025, 146,837 in 2030, 163,719 in 2035, and 179,288 in 2040. Second, the scenario for the retirement of baby boomers led to a decrease in the growth rate due to time delay. Third, Seoul and Gyeonggi-do account for a high percentage of demand, a very high upward trend was identified in Gyeonggi-do, and as a result, the projection showed that the demand of the physician workforce in Gyeonggi-do would worsen over time. Conclusion: This study is meaningful in that rational and collective physician workforce supply and demand and its imbalance in workforce distribution were verified through various projections by scenarios and regions of Korea with System Dynamics.

• KIEAE Journal
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• v.13 no.2
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• pp.77-84
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• 2013

Schools are one of favorable public buildings for Renewable Energy(RE) systems due to site conditions and their energy demand profiles(e.g. daytime-based use of hot water and heating/cooling). Although the government encourages schools to be equipped with RE systems, the adoption of RE systems in existing energy supply systems faces technical and financial barriers. For example, when installing a RE-based combination system(RECS) to meet the energy demand at various school scales, identifying cost effective combination of capacities of the RECS is not trivial since it usually requires technically intensive work including detailed simulation and demand/supply analysis with extensive data. This kind of simulation-based approaches is hardly implementable in practice. To address this, a simpler and applicable decision-supporting method is suggested in this study. This paper presents a simplified model in support of decision-making for optimal capacities of RECS within given budget scales and schools sizes. The proposed model was derived from detailed simulation results and statistical data. Using this model, the optimal capacities of RECS can be induced from the number of classes in a school.

• Journal of Climate Change Research
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• v.7 no.3
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• pp.341-349
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• 2016

This study is intended to set a greenhouse gas emission scenario based on green remodeling pilot project (Annex building of Seoul Customs Office) using LEAP model, a long-term energy plan analysis model, to calculate the energy saving and greenhouse gas emission till year 2035 as well as to analyze the effect of electric power saving cost. Total 4 scenarios were made, Baseline scenario, assuming the past trend is to be maintained in the future, green remodeling scenario, reflecting actual green remodeling project of Seoul Customs Office, behavior improvement and renewable energy supply, and Total scenario. According to the analysis result, the energy demand in 2035 of Baseline scenario was 6.1% decreased from base year 2013, that of green remodeling scenario was 17.5%, that of behavior improvement and renewable energy supply scenario was 21.1% and that of total scenario was 27.3%. The greenhouse emission of base year 2013 was $878.2tCO_2eq$, and it was expected $826.3tCO_2eq$, approx. 5.9% reduced, in 2035 by Baseline scenario. the cumulative greenhouse gas emission saving of the analyzing period were $-26.5tCO_2eq$ by green remodeling scenario, $2.8k\;tCO_2eq$ by behavior improvement and renewable energy supply scenario, and $2.0k\;tCO_2eq$ by total scenario. In addition the effect of electricity saving cost through energy saving has been estimated, and it was approx. 634 million won by green remodeling scenario and appro. 726 million won by behavior improvement and renewable energy supply scenario. So it is analyzed that of behavior improvement and renewable energy supply scenario would be approx. 12.7% higher than that of green remodeling scenario.

• The Korean Journal of Applied Statistics
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• v.22 no.5
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• pp.1019-1032
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• 2009

The city gas demand data has strong seasonality. Thus, the seasonality factor is the majority for the development of forecasting model for city gas supply amounts. Also, real city gas demand amounts can be affected by other factors; weekday effect, holiday effect, the number of validity day, and the number of consumptions. We examined the degree of effective power of these factors for the city gas demand and proposed a time-series model for efficient forecasting of city gas supply. We utilize the liner regression model with autoregressive regression errors and we have excellent forecasting results using real data.

• Journal of the Korean Institute of Gas
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• v.25 no.3
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• pp.16-26
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• 2021

The global warming problem has arose, the supply eco-friendly vehicles such as HFCEVs is increasing around world and Korea is fully supporting subsidies, tax cut to form an initial market for HFCEVs. The key to the safety of HFCEVs is pressure vessels stored hydrogen, and although these pressure vessels must be inspection regularly, the existing inspection stations are insufficient to meet the demand for inspection. Therefore, it is important to establishment of pressure vessels inspection station for safety management of HFCEVs. In this study, it estimates innovation coefficient, imitation coefficient in Bass model by using electric vehicle sales data, and foretasted the supply of HFCEVs by region & the demand for inspection by region using the Bass diffusion model. As a result, the inspection demand for pressure vessels in HFCEVs in 2040 was 690,759 units, and it was confirmed 191 new inspection stations and 1,124 inspectors were needed to prepare for this.