Earticle

본고는 학제적 연구로서, 기후변화로 인한 농업생산성 변화와 생산가변성 변화가지역별로 어떤 경제적 효과를 유발하는지를 한국형 농업부문모형을 구축해 분석한다. 기존 수리계획모형의 한계를 극복하고자 기준 연도에 있어서는 경제자료와최적화 모형의 해가 일치하도록 하는 Howitt(1995)의 실증적 수리계획법(PMP)을 적용하되, 시장균형조건을 도입하여 가격변수들을 내생화하며, Dixit(1989)이제안한 국내산과 수입산 소비재의 불완전대체관계도 모형에 반영한다. 분석결과2℃의 기온상승에 따른 국내 농업 총생산량 감소는 지역간 그리고 품목간 대체노력으로 인해 물리적 영향 평가 예측치보다는 적을 것으로 보이지만, 세부 품목별및 지역별로는 상당히 다른 생산효과가 발생할 것으로 예측되어, 향후 품목 및 지역별로 특화된 적응노력이 필요함도 확인된다.

The purpose of this interdisciplinary study is to evaluate the regional impactsof agricultural productivity change and the growing instability of agriculturalproduction using a Korean agricultural sector model. We apply the positivemathematical programming(PMP) approach of Howitt(1995), which has abuilt-in process of keeping the consistency between its model solutions and theobserved data. Moreover, our study makes output prices endogenous byincorporating market equilibrium conditions into the programming model, andallows imperfect substitution between imported and domestic foods followingthe specification of Dixit(1989). This study finds that substantial regional andcommodity substitution will occur in response to climate change, and hence,emphasizes the importance of regional and commodity specific adaptionmeasures.

The mobile access network designing provides an effective designing platform for entire mobile network. The mobile access network designing involves optimal assignment of communication link between components of the access network, satisfying various technical constraints of the network. Moreover, components of mobile access network are vulnerable to failure due to technical and environmental factors. Therefore, it is a critical problem, to define an effective mechanism for handling these faults at minimum cost while designing the mobile access network. In this paper we propose, heuristics based optimal fault tolerant algorithm to minimize the overall cost of mobile access network designing along with fault tolerant mechanism. Mathematical programming is used to formulate the problem. Further, six faults mechanisms are identified based on failure types, failure components at various access network level. These fault tolerant mechanism uses dual homing as the solution, in which case secondary link exists as backup along with primary communication between network components during link assignment of access network. The algorithm produces an optimal fault tolerant assignment of link satisfies the capacity and connectivity constraints of access network components. The algorithm outperforms well both in the smaller network and larger network.

This paper deals with the multiple attribute decision making problem when a decision maker incompletely articulates his/her preferences about the attribute weight and alternative value. Furthermore, we consider the attribute tree which is structured hierarchically. Techniques for establishing dominance with linear partial information are proposed in a hierarchically structured attribute tree. The linear additive value function under certainty is used in the model. The incompletely specified information constructs a feasible region of linear constraints and therefore the pairwise dominance relationship between alternatives leads to intractable non-linear programming. Hence, we propose solution techniques to handle this difficulty. Also, to handle the tree structure, we break down the attribute tree into sub-trees. Due to there cursive structure of the solution technique, the optimization results from sub-trees can be utilized in computing the value interval on the topmost attribute. The value intervals computed by the proposed solution techniques can be used to establishing the pairwise dominance relation between alternatives. In this paper, pairwise dominance relation will be represented as strict dominance and weak dominance, which ware already defined in earlier researches.

This paper presents three mathematical programming approaches to solving transshipment problems with interval supply and demand requirements. A linear goal programming model was developed based on the data obtained from a nationwide retail firm. Three mathematical programming model results were compared and analyzed, and three separate hypotheses were examined by using the Wilcoxon signed-ranked test for the model applicability. The test results were analyzed and interpreted for decision making.

The use of three mathematical programming techniques (quadratic programming, integer quadratic programming and linear programming) is discussed to solve some problems in linear regression analysis. When the criterion is the minimization of the sum of squared deviations and the parameters are linearly constrained, the problem may be formulated as quadratic programming problem. For the selection of variables to find "best" regression equation in statistics, the technique of integer quadratic programming is proposed and found to be a very useful tool. When the criterion of fitting a linear regression is the minimization of the sum of absolute deviations from the regression function, the problem may be reduced to a linear programming problem and can be solved reasonably well.ably well.

Usual symmetric duality results are proved for Wolfe and Mond-Weir type nondifferentiable nonlinear symmetric dual programs under F-convexity F-concavity and F-pseudoconvexity F-pseudoconcavity assumptions. These duality results are then used to formulate Wolfe and Mond-Weir type nondifferentiable minimax mixed integer dual programs and symmetric duality theorems are established. Moreover, nondifferentiable fractional symmetric dual programs are studied by using the above programs.

We discuss why sample design by mathematical programming can be beneficial to practical surveys. We illustrate some developments of software for sample design using mathematical programming in several statistical organizations. Also, we present certain restrictions on the use of mathematical programming.

신용평점을 위한 부도예측의 분류 문제를 다루는데 있어서 통계적 판별분석 및 인공신경망 및 유전자알고리즘 등을 이용한 데이터 마이닝의 방법들이 일반적으로 고려되어왔다. 이 연구에서는 수리계획법을 응용하여 classification gap을 고려한 이단계 수리계획 접근방법을 신용평가에 적용하는 방법론을 제안하여 수리계획법을 통한 신용평가모형 구축의 가능성을 제시한다. 1단계에서는 선형계획법을 이용해서 대출 신청자에게 대출을 허가할 것 인지의 여부를 결정하게 되는 대출 심사 filtering으로의 적용단계이고, 2단계에서는 정수계획법을 이용하여 오분류 비용이 최소가 되도록 하는 판별점수를 찾는 과정으로 모형을 구성한다. 개인 대출 신청자의 데이터(German Credit Data)에 대하여 피셔의 선형 판별함수, 로지스틱 회귀모형 및 기존의 수리계획 기법들과의 비교를 통해서 제안된 모델의 성능을 평가한다. 이단계 수리계획 접근법의 평가 결과를 통하여 신용평가모형에의 적용가능성을 기존 통계적인 접근방법 및 수리계획 접근법과 비교하여 제시하고 있다.

This paper develops an optimization model for portfolio allocations in 22 emerging equity markets by incorporating the conflicting objectives of maximizing return and minimizing risk in a single objective function. The resulting model allows users to input their risk aversion value to obtain the optimal portfolio mix. The model is extended to include minimum and maximum allocations per geographical region as well as minimum and maximum number ofmarkets per region, given that the investor desires to minimize portfolio risk with a minimum portfolio return to be achieved.

In work scheduling problems, scheduling constraints are not absolutely rigid; they may be changed depending on the scheduling aspect effected. In order to cope with changes in scheduling constraints and assignment strategies and to optimize scheduling results quickly, this paper will propose a new scheduling method which combines knowledge engineering and mathematical programming techniques.

Recently a new concept of shadow prices, called average shadow price, has been developed. This paper provides a dual problem and the corresponding duality theorems justifying this new shadow price. The general duality framework is used. As an important secondary result, a new reduced class of price function, the pp. h.-class, has been developed for the general duality theory. This should be distinguished from other known reductions achieved in some specific areas of mathematical programming, in that it sustains the strong duality property in all the mathematical programs. The new general dual problem suggested with this pp. h.-class provides, as an optimal solution, the average shadow prices.

Background: Resilience engineering (RE) is a new paradigm that can control incidents and reduce their consequences. Integrated RE includes four new factors-self-organization, teamwork, redundancy, and fault-tolerance-in addition to conventional RE factors. This study aimed to evaluate the impacts of these four factors on RE and determine the most efficient factor in an uncertain environment. Methods: The required data were collected through a questionnaire in a petrochemical plant in June 2013. The questionnaire was completed by 115 respondents including 37 managers and 78 operators. Fuzzy data envelopment analysis was used in different ${\alpha}$-cuts in order to calculate the impact of each factor. Analysis of variance was employed to compare the efficiency score means of the four abovementioned factors. Results: The results showed that as ${\alpha}$ approached 0 and the system became fuzzier (${\alpha}=0.3$ and ${\alpha}=0.1$), teamwork played a significant role and had the highest impact on the resilient system. In contrast, as ${\alpha}$ approached 1 and the fuzzy system went toward a certain mode (${\alpha}=0.9$ and ${\alpha}=1$), redundancy had a vital role in the selected resilient system. Therefore, redundancy and teamwork were the most efficient factors. Conclusion: The approach developed in this study could be used for identifying the most important factors in such environments. The results of this study may help managers to have better understanding of weak and strong points in such industries.

East Asian regional logistics is expected to grow rapidly. It may provide much more business opportunities for many countries within the region, on the other hand, it will create hot competition for market occupancy at the same time. Korea, China, and Japan, the key countries in East Asian region, have undertaken concerted efforts to improve their logistics sector, upgrade their infrastructure and technology to get a bigger slice of the market, especially in the filed of maritime and port. This paper presents the emperical measures of efficiency of 7 major Chinese ports, 3 major Korean ports, and 5 major Japanese ports along with the DEA and the Bootstrap method. In this paper, the container port service process is considered as a production process using five inputs (number of cranes, number of berths, length of berths, depth of berths, total area of container terminal) and generating one outputs (throughput). Through the analysis, we will investigate the efficiency of these major East Asian ports and figure out the trendof the efficiency.

The authors have been devoted to researches on fuzzy theories and their applications, especially control theory and application problems, for recent years. In this paper, the authors present results on a comparison of optimal solutions between ones of an ordinary-typed mathematical linear programming problem(O.M.I.P. problem) and ones of a Zimmerman-typed fuzzy mathematical linear programming problem (F.M.L.P. problem), and comment about the sensitivity (differences and fuzziness on between O.M.L.P. problem and F.M.L.P. problem) on optimal solutions of these mathematical linear programming problems.

노년층뿐만 아니라 청년층에 속하는 성인들 사이에서도 병원 외 심장정지(OHCA)를 겪는 심장질환자의 수가 증가하고 있다. 자동심장충격기(AED)는 병원 외 심장정지 환자의 생존율을 개선하는 데 있어 긴요하다. 심장정지 생존율은 제세동 시간에 대하여 지수적으로 감소(decline exponentially)하는 것으로 밝혀졌으나, 자동심장충격기의 최적 배치에 있어 심장정지 생존율의 이러한 특성을 반영한 국내 연구가 미미한 상황이다. 본 연구에서는 자동심장충격기의 최적 입지를 결정하기 위하여 exponential decay coverage 함수를 갖는 최대 gradual coverage 입지 모델에 대하여 고찰하였다. exponential decay coverage 함수는 심장정지 환자의 생존율에 대한 과다추정을 완화한다. 향후 시뮬레이션을 통하여 랜덤한 행인 위치 및 이동을 반영함으로써 행인의 심정지 대응에 있어 창발적인(emergent) 특징을 식별할 수 있는 시설 입지 모델이 개발될 것으로 예측된다.

The number of patients with cardiovascular diseases who experience an out-of-hospital cardiac arrest (OHCA) are increasing among young adults as well as the aged population. An automated external defibrillator (AED) is vital in improving survival rates of OHCA victims. Survival rates of OHCA were shown to decline exponentially in time to defibrillation, yet studies in Korea are uncommon that captures the properties of their survival rates in examining optimal locations of AEDs. In this study, we worked on the maximal gradual coverage location problem (MGCLP) with exponential decay coverage function to decide on their optimal locations. The exponential decay coverage function mitigates the drawback of over-estimating survival rates of OHCA patients. It is expected that a more sophisticated facility location problem will be developed to identify the "emergent" characteristics of pedestrians who responds to the OHCA occurrence by incorporating random pedestrian locations and movement through simulation.

혼동 행렬 (confusion matrix)은 자극 또는 인식대상(데이터)에 대한 반응을 데이터화함으로써 인식대상(데이터)의 특성분석을 통하여 복잡한 시스템을 효율적으로 통제, 관리하기 위한 분석기법에 사용된다. 클러스터링은 인식 시스템을 위한 기법으로서 다양한 분야에서 널리 활용되고 있다. 본 연구에서는 혼동 행렬을 이용한 최적화 모델을 통하여 클러스터링(Clustering) 문제의 새로운 접근법을 제시한다. 최근 수리 계획 분야에서 클러스터링 분야에 대한 연구가 계속되고 있는데 그러한 수리 모델과 혼동 행렬을 접목하여 새로운 모델을 제시한다.

본 연구는 의료비용 기반 수가를 산정할 때 가장 중요한 배부기준으로 사용하는 의사 행위시간에 대한 조사방식을 설문조사 방식과 자기기입 방식에서 과학적으로 개선하기 위한 것이다. 건강보험요양급여비용은 상대가치점수, 환산지수, 종별가산으로 구성된다. 상대가치점 수는 의사업무량, 진료비용, 위험도로 구성되고, 이 중 의사업무량은 시술시간과 분당 업무강도로 구성되어 있다. 따라서 건강보험요양급여비 용은 근본적으로 시술시간에 근거하여 결정된다. 하지만 시간은 의료행위를 수행하는데 걸리는 실제 소요시간을 측정하여 사용하여야 하지만 현재 시술시간은 의료행위 정의 기술서에 따라 설문조사의 형태로 낮은 빈도로 조사가 이루어져 신뢰성에 대한 의문이 존재한다. 건강보험요 양급여비용은 과학적인 데이터에 근거하여 이루어져야 하지만 데이터의 정확성에 대한 확신이 떨어지다 보니 관련 집단의 이해관계에 의해 결정이 될 가능성이 존재한다. 그렇기 때문에 이를 과학적으로 측정해야 하며, 본 연구에서는 의과의원 의료비용을 행위별수가 단위로 배부할 때 주요한 기준인 수가시간을 자기기입 방식이 아닌 내과의원에서 발생한 수가행위코드의 발생건수를 바탕으로 수리계획 모형을 사용하여 공학적으로 추정하였다. 최근 행위별수가제 하에 건강보험 재정이 점차 악화됨에 따라 새로운 지불제도 및 상대가치점수 개선 요구로 인해 수가시간의 중요성이 더욱 높아짐을 대비하고자 하였다. 본 연구의 구체적인 분석결과는 다음과 같다. 첫째 내과 의원의 의사 행위코드에서 초진료의 추정시간이 가장 큰 추정치로 나타났다. 둘째 재진료보다 초진료 추정시간이 길게 나타났다. 셋째 가장 낮은 추정시간은 당검사 반정량 검체 행위코드이다. 본 연구의 결과는 우리가 알고 있는 일반적 시간과 유사한 결과가 나타났으며, 이는 앞으로 공학적 방식으로 수가시간의 사용 가능성을 입증한 것이다.

This study aims to scientifically improve the self-recording method of the questionnaire, which is the most important method for calculating medical cost-based fees. This study addresses the increasing demand for an improved payment system and refined relative value scales, as the financial sustainability of Korea’s fee-for-service (FFS) health insurance system faces growing challenges. Recognizing the critical role of service time estimates (an essential cost allocation criterion for medical expenses) in establishing a cost-based fee schedule, this research employs a mathematical programming model to estimate service times scientifically, using billing codes and occurrence data from internal medicine clinics instead of self-reported methods. Key findings of this study are as follows: first, initial consultation services show the highest estimated service time; second, initial consultations require longer time than follow-up visits; and third, the lowest estimated time was observed in glucose testing (semi-quantitative) codes. These results align with common expectations, demonstrating the feasibility of accurately estimating service times using engineering-based approaches. This study’s findings not only validate general assumptions about consultation durations but also provide foundational evidence for the application of engineering methods in calculating service times for healthcare services in Korea.

바이오에너지는 탄소중립을 추구하는 방안 중 하나로 간주되고 있다. 그러나 수확된 식물 바이오매스를 연소하면 필연적으로 대기 중 이산화탄소는 일정기간 동안 화석을 연소할 때보다 더 많아진다. 본 논문에서는 이 탄소부채의 총량과 상환기간을 예측하고 최소화하는 방법을 제안한다. 사례연구로는 현재 사용되고 있는 화석연료를 바이오매스로 일시에 전환할 경우에 대한 탄소순환 영향평가를 수행한다. 이를 통해 탄소중립 개념의 근본적인 취약성을 지적한다. 바이오에너지의 지속가능성을 위한 실행방안으로는 숲 면적 감소분에 비례하는 추가식림 및 숲 질량 증가분에 비례하는 추가수확 공식을 제안하였다. 최적화 결과, 탄소부채 상환기간은 약 70년, 대기 중 이산화탄소는 최대 50% 이상, 정상상태에서 3% 증가가 예상된다. 이는 이론적으로 예측한 최상의 결과이며 실제로는 이보다 나쁠 것으로 추정된다. 따라서 바이오매스는 진정으로 탄소 중립적이지 않으며, 화석연료의 대체에너지원으로서 부적합하다. 본 연구에서 제안된 방법은 이미 사용 중인 바이오에너지의 현재 및 미래 탄소부채 최소화를 통해 탄소중립으로의 접근에 기여할 수 있을 것으로 예상된다.

Bioenergy is generally considered to be one of the options for pursuing carbon neutrality. However, for a period of time, combustion of harvested plant biomass inevitably causes more carbon dioxide in the atmosphere than combustion of fossil fuels. This paper proposes a method that predicts and minimizes the total amount and payback period of this carbon debt. As a case study, a carbon cycle impact assessment was performed for immediate switching of the currently used fossil fuels to biomass. This work points out a fundamental vulnerability in the concept of carbon neutrality. As an action plan for the sustainability of bioenergy, formulas for afforestation proportional to the decrease in the forest area and surplus harvest proportional to the increase in the forest mass are proposed. The results of optimization indicate that the carbon debt payback period is about 70 years, and the carbon dioxide in the atmosphere increases by more than 50% at a maximum and 3% at a steady state. These are theoretically predicted best results, which are expected to be worse in reality. Therefore, biomass is not truly carbon neutral, and it is inappropriate as an energy source alternative to fossil fuels. The method proposed in this work is expected to be able to contribute to the approach to carbon neutrality by minimizing present and future carbon debt of the bioenergy that is already in use.