• 무역학회지
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• 제46권2호
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• pp.213-228
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• 2021

In recent year, US government requires local investment ,unlike in the past, when import restrictions and tariff were imposed. In this situation, many companies are considering new investment in the US and entering the local market. However, research on the optimal investment plan along with the case analysis on trade regulation is extremely limited and more research needs to be conducted. Accordingly, this study aims to suggest the implications and countermeasure of the SCM and logistical perspective by studying the optimal measures for the new investment of each company due to trade regulation. As a research method, the gravity location model, Mixed Integer Linear Programming Model were used to select the optimal automobile manufacturing factory considering each state's population. This study will be implication of SCM and logistics perspective not only for companies considering new investment in the US but also for the government to conduct trade negotiations. In the future, it is expected that the US trade pressure will increase and affect Korea in many ways. Therefore, in order to cope with such difficult situation in a timely manner, continuous research considering various possibilities is needed in the future.

• 대한산업공학회지
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• 제23권1호
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• pp.39-54
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• 1997

This paper presents four process models for machining processes : 1) an economical mathematical model of machining process, 2) a prediction model for surface roughness, 3) a decision model for fuzzy cutting conditions, and 4) a judgment model of machinability with automatic selection of cutting conditions. Each model was developed the economic machining, and these models were applied to theories widely studied in industrial engineering which are nonlinear programming, computer simulation, fuzzy theory, and neural networks. The results of this paper emphasize the human oriented domain of a nonlinear programming problem. From a viewpoint of the decision maker, fuzzy nonlinear programming modeling seems to be apparently more flexible, more acceptable, and more reliable for uncertain, ill-defined, and vague problem situations.

• KIEAE Journal
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• 제2권4호
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• pp.65-72
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• 2002

In this study, the evaluation of environmental performance of the building energy system of domestic commercial sector was carried out. Based on the theory of linear programming model, we established an evaluation model satisfying object functions and constraint conditions. Employing the model, the evaluation of building energy system was performed under the consideration of cost and environmental constraint conditions. As an evaluation tool, MARKAL (MARKet Allocation) known as a market distribution model was employed. We analyzed scenarios of Case I (Base Scenarios) through Case IX established by the combination of the components of building energy system such as glazing, building skin, core, and heat source system. According to the results of the evaluation, highest contribution on the useful energy demand was obtained from the building energy system combined with solar heat source system, when the total amounts of $CO_2$ exhaust as an environmental constraint condition is assumed to be the level of 1995.

• 한국수자원학회논문집
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• 제34권5호
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• pp.473-486
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• 2001

WGR 강우모형은 중규모 정도의 강우를 표현하기 위해 개발된 개념적인 모형으로 대기의 동역학적 특성과 강우의 통계학적 특성이 비교적 잘 반영된 모형이다(Waymire 등, 1984). 그러나 이 모형은 최대 18개의 매개변수르 가지며 모형의 구조가 강한 비선형성을 가지고 있어 매개변수 추정이 매우 어려운 문제로 남아 있다. 지금까지 각각 다른 지역의 강우에 대해 비선형 최적화 기법(non-linear programming; NLP)을 이용하여 매개변수를 추정한 예가 있으나 그 과정 자체가 매우 복잡하여 이 모형을 다른 목적으로 이용하는데 문제로 지적되고 있다. 본 연구에서는 유전자 알고리즘(genetic algorithm; GA)을 이용한 WGR 모형의 매개변수 추정법을 제시하였으며, 이를 한강유역에 적용하여 NLP에 의한 결과 (Yoo와 Kwon, 2000)와 비교하였다. 적용 결과 GA는 NLP에 비해 상대적으로 작은 SSE(sum of square error)를 나타내었고 계절의 변화에 보다 일관적인 반응을 보임을 알 수 있었다. 또한 추정된 매개변수 분석결과, 여름철의 높은 강우량은 강우 세포의 강도보다는 강우전선의 도달율과 밀접한 관계가 있는 것으로 나타났다.

• 한국항해학회지
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• 제24권5호
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• pp.385-395
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• 2000

In the transportation literature, many useful decision making models for ship routing and ship scheduling have been studied. But the majority of these studies are on industrial carriers, bulk carriers, or tankers. It is quite recent that a few optimization models have been developed for liner fleet routing and scheduling problems. However there have been few academic studies on decision making models for the routing or scheduling problems of passenger ships in spite of their economic importance in the entire shipping industry. The purpose of this study is to develop analytic decision making models for ship routing and scheduling for the passenger ship fleet. This study gives two optimization models, one is a linear programming model and the other a goal programming model. These two models are solved easy by commercial linear programming softwares and suggest optimal ship routing plans and many other useful implications for passenger ship fleet managers.

• 융합경영연구
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• 제4권1호
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• pp.1-8
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• 2016

The purpose of this paper is to discuss the methodology of optimizing delivery route scheduling using a capacity integer linear programming problem model developed to a previous case study. The methodology suggests a two-stage decision: the first, automatic, where the manager will obtain guidance generated by the solution of the linear programming model, later they could use post-optimization techniques to fine tune to the best operational solution. This study has the goal to reduce the size of service companies' ground transportation fleets, aiming not only to reduce costs and increase competitive advantages but also to lower levels of air pollution and its consequences, traffic and, therefore, the levels of carbon dioxide, allowing for a reduction in envir onmental disasters.

• 대한산업공학회지
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• 제32권2호
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• pp.74-81
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• 2006

In this paper, we deal with the separation of data by concurrently determined, piecewise nonlinear discriminant functions. Toward the end, we develop a new $l_1$-distance norm error metric and cast the problem as a mixed 0-1 integer and linear programming (MILP) model. Given a finite number of discriminant functions as an input, the proposed model considers the synergy as well as the individual role of the functions involved and implements a simplest nonlinear decision surface that best separates the data on hand. Hence, exploiting powerful MILP solvers, the model efficiently analyzes any given data set for its piecewise nonlinear separability. The classification of four sets of artificial data demonstrates the aforementioned strength of the proposed model. Classification results on five machine learning benchmark databases prove that the data separation via the proposed MILP model is an effective supervised learning methodology that compares quite favorably to well-established learning methodologies.

• 한국방재학회 논문집
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• 제1권3호
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• pp.73-82
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• 2001

본 연구에서는 선형모형인 Nash 모형(1957)과 비 선형모형인 Diskin 모형(1964)의 매개변수를 최적화 기법을 사용하여 구하고 모형의 적용성을 검토하였다. 최적화 기법 중에서 최근 들어 활발히 연구되고 있는 유전자 알고리즘(Genetic Algorithm)과 비선형 계획법(Non-linear Programming)을 사용하여 Nash 모형과 Diskin 모형의 매개변수를 추정하였으며, 이를 소양강댐 유역의 호우사상에 적용하여 보았다. Nash 모형과 Diskin 모형에서 각각 유전자 알고리즘과 비 선형 계획법으로 구한 매개변수는 다소의 차이를 나타내며, 유전자 알고리즘과 비선형 계획법을 이용하여 Diskin 모형의 매개변수를 구하여 모의된 유출 수문곡선이 유전자 알고리즘과 비선형 계획법을 이용하여 Nash 모형의 매개변수를 구하여 모의된 유출수문곡선에 비해 실제 유출수문곡선에 더 근접한 결과를 나타냈으며 특히, 첨두치를 더 정확히 모의하였다.

• 한국경영과학회지
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• 제3권2호
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• pp.95-108
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• 1978

This paper discusses an application of mathematical programming techniques in the paper industry in determining optimal parent roll widths. Parent rolls are made from the reels produced at wide paper machines by slitting them to more manageable widths. The problem is finding a set of the slitting patterns that will minimize the trim loss involved in the sheeting operation. Two programming models, one linear and one mixed integer linear, are presented in this paper. Also presented are the computational experience, the model sensitivity, and the comparison of the optimal solutions with the simulated operational data.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1989년도 추계학술대회 논문집 학회본부
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• pp.191-193
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• 1989

This paper presents a optimal Var allocation algorithm for minimizing power loss and improving voltage profile in a given system. In this paper, nodal input data is considered as Gaussian distribution with their mean value and their variance. A stochastic Linear Programming technique based on chance constrained method is applied to solve the probabilistic constraint. The test result in IEEE-14 Bus model system showes that the voltage distribution of load buses is improved and the power loss is more reduced than before Var allocation.