• Title/Summary/Keyword: 비용-손실 모형

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The Development of Optimal Path Model for Transport of Hazardous Materials (위험물 소송을 위한 최적경로모형 개발)

  • 조용성;오세창
    • Proceedings of the KOR-KST Conference
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    • 1998.10b
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    • pp.508-508
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    • 1998
  • 위험물 차량사고는 일반차량의 교통사고시 발생하는 인명피해, 재산피해, 교통지체 외에 부가적으로 환경적 영향에 의한 엄청난 인명 및 재산손실을 유발시킬 수 있다. 따라서 이러한 위험물차량사고를 예방하고 피해를 최소로 줄이기 위해서는 위험물수송경로의 신중하고 체계적인 결정이 필수적이라 할 수 있다. 외국의 경우, 위험물의 방출이 미치는 환경적 영향에 대한 인식이 확대되면서 위험물 수송시 응급처리에 관한 연구, 위험물 수송에 따른 위험도 평가에 관한 연구, 위험물 수송시 고려해야할 여러 조건에 관한 연구, 위험물 수송경로 설정에 관한 연구 등이 진행되고 있다. 반면에 우리 나라는 위험물차량관리와 사고처리에 대해 실시간적인 관리를 목표로 하는 국가차원의 계획을 수립하고는 있지만, 현재 이와 관련된 연구는 거의 없는 실정이다. 앞으로 산업발달에 따른 위험물수송량의 증가와 환경의식의 변화에 따라 위험물수송 및 사고처리 등에 관한 연구가 필요할 것이다. 따라서, 본 연구는 위험물차량의 운송경로를 결정할 때 고려해야 할 여러 가지의 기준 및 목표에 따라 위험물수송경로를 설정하는 모형을 제시함으로써 위험물수송에 수반되는 위험을 최소화하면서 위험물차량의 통행시간, 거리, 비용 등을 최적화하여 위험물수송의 안전 및 운영효율성을 향상시키고자 한다. 먼저, 위험물 수송경로의 기준지표로 사용될 위험도를 산정하기 위해 링크 주변노출인구, 밀도 등을 변수로 하는 모형식을 제안하고, 두 번째로 산정된 위험도를 기반으로 최적경로를 결정하는 알고리즘을 제안하였다. 마지막으로 가상 네트웍에 본 연구에서 제안된 모형을 적용하고 현재 일반적으로 사용되는 최단경로와 비교·분석하였다.것은 운송거리와 운송비용이 각각 주요한 변수라는 것이다. 모형의 타당성을 검증하기 위해서는 logilikelihood 값을 구하여 $\rho$^2분석을 시행하였다. 여기서는 각 품목별로 $\rho$^2값이 약 0.15~0.3의 비교적 높은 수치를 보여주고 있으므로 모형의 설명력이 어느 정도 있다는 것이 아울러 증명이 되었다. 상관관계에 대한 분석에서는 영업용 차량간의 상관관계가 높게 나타났으며, 이는 곧 영업용 화물차량을 적재중량별로 구분하는 것이 별 의미가 없음을 의미한다. 다시 말하면 자가용 차량을 보유하고 있지 않은 회사는 다른 운송전문업체에 화물운송을 의뢰하게 되므로 출하중량에 따라 화물차량을 구분하는 것에 대해서 그다지 큰 고려를 하지 않는 것으로 해석할 수가 있다.적합함을 재확인함. 6. 혼잡초기를 제외한 혼잡기간 중 대기행렬길이는 밀도데이터 없이도 혼잡 상류부의 도착교통량과 병목지점 본선통과교통량만을 이용하여 추정이 가능함. 7. 이상에 연구한 결과를 토대로, 고속도로 대기행렬길이를 산정할 수 있는 기초적인 도형을 제시함.벌레를 대상으로 처리한 Phenthoate EC가 96.38%의 방제가로 약효가 가장 우수하였고 3월중순 및 4월중순 월동후 암컷을 대상으로 처리한 Machine oil, Phenthoate EC 및 Trichlorfon WP는 비교적 약효가 낮았다.>$^{\circ}$E/$\leq$30$^{\circ}$NW 단열군이 연구지역 내에서 지하수 유동성이 가장 높은 단열군으로 추정된다. 이러한 사실은 3개 시추공을 대상으로 실시한 시추공 내 물리검층과 정압

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Effectiveness Evaluation of Demand Forecasting Based Inventory Management Model for SME Manufacturing Factory (중소기업 제조공장의 수요예측 기반 재고관리 모델의 효용성 평가)

  • Kim, Jeong-A;Jeong, Jongpil;Lee, Tae-hyun;Bae, Sangmin
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.18 no.2
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    • pp.197-207
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    • 2018
  • SMEs manufacturing Factory, which are small-scale production systems of various types, mass-produce and sell products in order to meet customer needs. This means that the company has an excessive amount of material supply to reduce the loss due to lack of inventory and high inventory maintenance cost. And the products that fail to respond to the demand are piled up in the management warehouse, which is the reality that the storage cost is incurred. To overcome this problem, this paper uses ARIMA model, a time series analysis technique, to predict demand in terms of seasonal factors. In this way, demand forecasting model based on economic order quantity model was developed to prevent stock shortage risk. Simulation is carried out to evaluate the effectiveness of the development model and to demonstrate the effectiveness of the development model as applied to SMEs in the future.

A Trade Effect Analysis of the Introducing the Euro in the Members of the Eurozone (유로존 국가들의 유로화 도입으로 인한 무역효과 분석)

  • Kang, Bo-Kyung
    • International Area Studies Review
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    • v.14 no.1
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    • pp.203-219
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    • 2010
  • Nowadays an instability of the exchange rate on accounts of global finance crisis brings on a lot of an economic damage such as recession, decreasing of total trade and so on. However some countries which belong to be membership of the eurozone could escape economic slump shortly and easier than others. The reason for this is that they share with the Euro as a their own currency which is the second vehicle currency all of the world. This paper analyzes the correlation of joining the Euro zone and trade with pooled OLS, random effect estimation, and fixed effect estimation. A membership of the Euro zone are able to increase trade 11.3% ~ 25.3% one another on average since some country belongs to the Euro zone. It is very important for some countries which have a plan to affiliate the Euro zone sooner or later to realize economic effect because of a protection of the Euro zone as well as political power.

Economic Feasibility Analysis of Marine Ecosystem Restoration Technology Program (해양생태계 복원기술개발 사업의 경제적 타당성 분석)

  • Kwon, Young-Ju;Paik, Sang-Kyu;Yoo, Seung-Hoon
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.20 no.2
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    • pp.130-142
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    • 2014
  • The Korean government is considering implementation of the marine ecosystem restoration technology program (MERTP) to analyze the current status of the marine ecosystems and causes for the ecosystem deterioration as well as to eventually establish a master strategic plan for restoring ecosystem functions and preventing ecosystem functional loss. In order to determine likelihood of successful implementation, it is essential to perform an analysis of the economic feasibility of the program. The present study assessed economic feasibility of the MERTP. To this end, the dichotomous choice contingent valuation (CV) method is used. In particular, dichotomous choice (DC) format is employed as a method of eliciting willingness-to-pay (WTP) response to incentive-compatible mechanisms. The study also employed the spike model to deal with zero WTP responses from the DC CV survey. This survey of 1,000 randomly selected households in accordance with the guidelines provided by the National Oceanic and Atmospheric Administration (USA) was carried out nationwide in 2013. And, the respondents were asked in person-to-person interviews about their WTP for implementing the MERTP. The results showed that the annual mean WTP was estimated to be 5,414 won per household. Consequently, the annual benefit from the MERTP would be about 98.6 billion won for the next five years. Economic feasibility assessment utilizing the MERTP investment cost and expansion cost of the value provided that net present value, benefit/cost ratio, and internal rate of return are 337.8 billion won, 5.20, and 65.9 %, respectively, which are bigger than 0, 1.0, and 5.5 %, and that the MERTP passes the cost-benefit analysis.

Development of Hazard-Level Forecasting Model using Combined Method of Genetic Algorithm and Artificial Neural Network at Signalized Intersections (유전자 알고리즘과 신경망 이론의 결합에 의한 신호교차로 위험도 예측모형 개발에 관한 연구)

  • Kim, Joong-Hyo;Shin, Jae-Man;Park, Je-Jin;Ha, Tae-Jun
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.30 no.4D
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    • pp.351-360
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    • 2010
  • In 2010, the number of registered vehicles reached almost at 17.48 millions in Korea. This dramatic increase of vehicles influenced to increase the number of traffic accidents which is one of the serious social problems and also to soar the personal and economic losses in Korea. Through this research, an enhanced intersection hazard prediction model by combining Genetic Algorithm and Artificial Neural Network will be developed in order to obtain the important data for developing the countermeasures of traffic accidents and eventually to reduce the traffic accidents in Korea. Firstly, this research has investigated the influencing factors of road geometric features on the traffic volume of each approaching for the intersections where traffic accidents and congestions frequently take place and, a linear regression model of traffic accidents and traffic conflicts were developed by examining the relationship between traffic accidents and traffic conflicts through the statistical significance tests. Secondly, this research also developed an intersection hazard prediction model by combining Genetic Algorithm and Artificial Neural Network through applying the intersection traffic volume, the road geometric features and the specific variables of traffic conflicts. Lastly, this research found out that the developed model is better than the existed forecasting models in terms of the reliability and accuracy by comparing the actual number of traffic accidents and the predicted number of accidents from the developed model. In conclusion, it is expect that the cost/effectiveness of any traffic safety improvement projects can be maximized if this developed intersection hazard prediction model by combining Genetic Algorithm and Artificial Neural Network use practically at field in the future.

A Study on the Optimization Problem for Offshore Oil Production and Transportation (해양 석유 생산 및 수송 최적화 문제에 관한 연구)

  • Kim, Chang-Soo;Kim, Si-Hwa
    • Journal of Navigation and Port Research
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    • v.39 no.4
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    • pp.353-360
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    • 2015
  • The offshore oil production requires a huge amount of cost and time accompanied by multiple variables due to the peculiar nature of 'offshore'. And every process concerned is controlled by elaborate series of plans for reducing loss of lives, environment and property. This paper treats an optimization problem for offshore oil production and transportation. We present an offshore production and transportation network to define scope of the problem and construct a mixed integer linear programming model to tackle it. To demonstrate the validity of the optimization model presented, some computational experiments based on hypothetical offshore oil fields and demand markets are carried out by using MS Office Excel solver. The downstream of the offshore production and transportation network ends up with the maritime transportation problem distributing the crude oil produced from offshore fields to demand markets. We used MoDiSS(Model-based DSS in Ship Scheduling) which was built to resolve this maritime transportation problem. The paper concludes with the remark that the results of the study might be meaningfully applicable to the real world problems of offshore oil production and transportation.

A Development of an Optimal Feeder-Bus Service Area (연계버스 서비스권역 결정에 관한 연구)

  • Rhee, Sung-Mo
    • Journal of Korean Society for Geospatial Information Science
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    • v.3 no.2 s.6
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    • pp.199-211
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    • 1995
  • Bus, Which is together with subway the main part of public transportation modes in the city, is reviewed for the development of an optimal feeder-bus service area. Based on the IDRISI of GIS package, and taking into account of the convenience of downtown-oriented public transportation users at peak time, a model for the development of feeder-bus service area and a solution and introduced. Major result in this study is as follows: Development is given to a model that is designed to overcome the shortage of the existing models, which has limits in simulating the real situation; Variables were used in combination so that bus and subway route, station spacing, and operating frequency can be determined simultaneously, which enables to elucidate the mutual relationship and the structure in public transportation system. A model for feeder-bus area development is also given applied to determination and opening of subway and urban express bus route and new transportation systems. The model developed in this paper is useful in the case of extension and opening of subway and urban express bus route and new transportation Systems.

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An Optimization Model for O&M Planning of Floating Offshore Wind Farm using Mixed Integer Linear Programming

  • Sang, Min-Gyu;Lee, Nam-Kyoung;Shin, Yong-Hyuk;Lee, Chulung;Oh, Young-Jin
    • Journal of the Korea Society of Computer and Information
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    • v.26 no.12
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    • pp.255-264
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    • 2021
  • In this paper, we propose operations and maintenance (O&M) planning approach for floating offshore wind farm using the mathematical optimization. To be specific, we present a MILP (Mixed Integer Linear Programming that suggests the composition of vessels, technicians, and maintenance works on a weekly basis. We reflect accessibility to wind turbines based on weather data and loss of power generation using the Jensen wake model to identify downtime cost that vary from time to time. This paper also includes a description of two-stage approach for maintenance planning & detailed scheduling and numeric analysis of the number of vessels and technicians on the O&M cost. Finally, the MILP model could be utilized in order to establish the suitable and effective maintenance planning reflecting domestic situation.

Corporate Credit Rating based on Bankruptcy Probability Using AdaBoost Algorithm-based Support Vector Machine (AdaBoost 알고리즘기반 SVM을 이용한 부실 확률분포 기반의 기업신용평가)

  • Shin, Taek-Soo;Hong, Tae-Ho
    • Journal of Intelligence and Information Systems
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    • v.17 no.3
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    • pp.25-41
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    • 2011
  • Recently, support vector machines (SVMs) are being recognized as competitive tools as compared with other data mining techniques for solving pattern recognition or classification decision problems. Furthermore, many researches, in particular, have proved them more powerful than traditional artificial neural networks (ANNs) (Amendolia et al., 2003; Huang et al., 2004, Huang et al., 2005; Tay and Cao, 2001; Min and Lee, 2005; Shin et al., 2005; Kim, 2003).The classification decision, such as a binary or multi-class decision problem, used by any classifier, i.e. data mining techniques is so cost-sensitive particularly in financial classification problems such as the credit ratings that if the credit ratings are misclassified, a terrible economic loss for investors or financial decision makers may happen. Therefore, it is necessary to convert the outputs of the classifier into wellcalibrated posterior probabilities-based multiclass credit ratings according to the bankruptcy probabilities. However, SVMs basically do not provide such probabilities. So it required to use any method to create the probabilities (Platt, 1999; Drish, 2001). This paper applied AdaBoost algorithm-based support vector machines (SVMs) into a bankruptcy prediction as a binary classification problem for the IT companies in Korea and then performed the multi-class credit ratings of the companies by making a normal distribution shape of posterior bankruptcy probabilities from the loss functions extracted from the SVMs. Our proposed approach also showed that their methods can minimize the misclassification problems by adjusting the credit grade interval ranges on condition that each credit grade for credit loan borrowers has its own credit risk, i.e. bankruptcy probability.

Impact Assessment of Vegetation Carbon Absorption and Economic Valuation Under Long-term Non-executed Urban Park Development (장기미집행공원 개발에 따른 도시 식생 탄소 흡수량에 미치는 영향 및 경제적 가치 평가)

  • Sung, Woong-Gi;Choi, Jae-Yeon;Yu, Jae-Jin;Kim, Dong-Woo;Son, Seung-Woo
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.21 no.10
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    • pp.361-371
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    • 2020
  • Since the implementation of the sunset law in 2020, concerns have been raised over the reckless development of long-term non-executed urban parks. In this study, the FSDAF method and CASA-NPP model were used to evaluate the annual average NPP of long-term non-executed urban parks in Seoul. Based on this, the carbon loss and economic value were assessed under five development scenarios. The total NPP value of long-term non-executed urban parks, except for the greenbelt area in Seoul, was 4,892.18 t C. In the first scenario, the NPP and cost were 4,892.18 t C of vegetation carbon and 1.18 billion won, 2,548.55 t C of vegetation carbon and 615 million won in the second scenario, 238.94 t C of vegetation carbon and 58 million won in the third scenario, 848.38 t C of vegetation carbon and 205 million won in the fourth scenario, and 1,596.00 t C of vegetation carbon and 385 million won in the fifth scenario. These results are meaningful for evaluating vegetation carbon and economic value loss according to five different development scenarios. The results of this study are expected to be useful for the preparation of measures to minimize the impact of the development of long-term non-executed urban parks.