• Journal of applied mathematics & informatics
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• 제8권2호
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• pp.439-448
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• 2001

In this paper a fuzzy linear programming problem is presented. Then using the concept of comparison of fuzzy numbers, by the aid of the Mellin transform, we introduce a method for solving this problem.

• 전자통신동향분석
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• 제35권5호
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• pp.134-138
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• 2020

Blockchain is an enabling technology for managing data with high trust and transparency among connected computers. Blockchain emerged with the advent of the Bitcoin cryptocurrency, and then, evolved as general-purpose platforms such as Ethereum, EOS, R3 Corda, and IBM Hyperledger Fabric. The application of blockchain covers a broad range of areas such as fintech, decentralized identity, distribution, real estate trading, games, and drone air traffic management. Smart contracts are indispensable for constructing blockchain services. This survey classifies smart contract languages by their features and shows their differences from existing general-purpose programming languages.

• Management Science and Financial Engineering
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• 제12권1호
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• pp.113-125
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• 2006

Bilevel programming problem is a two-stage optimization problem where the constraint region of the first level problem is implicitly determined by another optimization problem. In this paper we consider the bilevel quadratic/linear fractional programming problem in which the objective function of the first level is quasiconcave, the objective function of the second level is linear fractional and the feasible region is a convex polyhedron. Considering the relationship between feasible solutions to the problem and bases of the coefficient submatrix associated to variables of the second level, an enumerative algorithm is proposed which finds a global optimum to the problem.

• Management Science and Financial Engineering
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• 제13권2호
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• pp.1-27
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• 2007

This paper presents a fuzzy-goal programming(FGP) approach for Bi-Level Linear Multiple Objective Decision Making(BLL-MODM) problem in a large hierarchical decision making and planning organization. The proposed approach combines the attractive features of both fuzzy set theory and goal programming(GP) for MODM problem. The GP problem has been developed by fixing the weights and aspiration levels for generating pareto-optimal(satisfactory) solution at each level for BLL-MODM problem. The higher level decision maker(HLDM) provides the preferred values of decision vector under his control and bounds of his objective function to direct the lower level decision maker(LLDM) to search for his solution in the right direction. Illustrative numerical example is provided to demonstrate the proposed approach.

• 대한조선학회논문집
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• 제42권6호
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• pp.654-665
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• 2005

In this paper, we present a non-linear integer programming by genetic algorithm (GA) for available sizes of stiffener or thickness of plate in a job site. GA can rapidly search for the approximate global optimum under complicated design environment such as ship. Meanwhile it can handle the optimization problem involving discrete design variable. However, there are many parameters have to be set for GA, which greatly affect the accuracy and calculation time of optimum solution. The setting process is hard for users, and there are no rules to decide these parameters. In order to overcome these demerits, the optimization for these parameters has been also conducted using GA itself. Also it is proved that the parameters are optimal values by the trial function. Finally, we applied this method to compass deck of ship where the vibration problem is frequently occurred to verify the validity and usefulness of nonlinear integer programming.

• 한국생산제조학회지
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• 제24권3호
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• pp.327-333
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• 2015

As industrial robots come into wider use, their control techniques are being developed along with enhancements in their performance. Specially, the dynamic performance of a 6-axis articulated industrial robot is greatly changed according to the position and orientation of the robot. This means that the PI parameter tuning of the robot and orientation of the robot. This mconsidering the dynamic characteristics of robot mechanism. In this study, $LabView^{(R)}$ programming was applied to automatically conduct parameter scheduling for various robot motions. Using forward and inverse kinematics of RS2, we can divide the working envelope of RS2 into 24 subspaces. We then conduct the gain-tuning according to each subspace. Finally, we program the actual gain scheduling, in which the optimized gain-tuning for each subspace to be passed should be changed for various robot motions using $LabView^{(R)}$.

• 미생물학회지
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• 제35권2호
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• pp.121-127
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• 1999

염기서열 해독작업에서 각 핵산 단편을 조립하는 contig 구성문제에 활용이 가능한 computer program을 개발하였다. 본 프로그램은 국내에서 광범위하게 사용되고 있는 MS-Windows 운영체제의 개인용 컴퓨터에서 작동이 가능하며, GenBank, FASTA, ASCII 등과 같은 다양한 형태의 염기서열 자료를 입력할 수 있다. 두 단편에서 최대 유사도를 나타내는 부분을 정렬하는 작업에는 염기서열의 국부적 상동성을 계산하고 dynamic programming 알고리즘을 적용하는 방법을 이용하였다. 또한 사용하기 편리한 그래픽 방식의 인터페이스를 제공하여 초보자라도 손쉽게 조작할 수 있다는 장점을 갖는다. 본 프로그램의 성능을 검증하기 위하여 세균과 곰팡이로부터 해독된 16S rRNA 와 18S rRNA 유전자의 단편 염기서열을 재구성하는 작업에 프로그램을 사용하였을 때에 효율적인 작업이 가능하였다.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2020년도 학술발표회
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• pp.171-171
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• 2020

Decision making strategies should consider both adaptiveness and robustness in order to deal with two main characteristics of climate change: non-stationarity and deep uncertainty. Especially, robust strategies are different from traditional optimal strategies in the sense that they are satisfactory over a wider range of uncertainty and may act as a key when confronting climate change. In this study, a new framework named Robust Stochastic Dynamic Programming (R-SDP) is proposed, which couples previously developed robust optimization (RO) into the objective function and constraint of SDP. Two main approaches of RO, feasibility robustness and solution robustness, are considered in the optimization algorithm and consequently, three models to be tested are developed: conventional-SDP (CSDP), R-SDP-Feasibility (RSDP-F), and R-SDP-Solution (RSDP-S). The developed models were used to derive optimal monthly release rules in a single reservoir, and multiple simulations of the derived monthly policy under inflow scenarios with varying mean and standard deviations are undergone. Simulation results were then evaluated with a wide range of evaluation metrics from reliability, resiliency, vulnerability to additional robustness measures. Evaluation results were finally visualized with advanced visualization tools that are used in multi-objective robust decision making (MORDM) framework. As a result, RSDP-F and RSDP-S models yielded more risk averse, or conservative, results than the CSDP model, and a trade-off relationship between traditional and robustness metrics was discovered.

• 기술혁신연구
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• 제7권2호
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• pp.21-36
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• 1999

This paper presents a R&D investment model for Information and telecommunications (I&T) technology, which can be used by group decision makers, using multiple objective linear programming (MOLP). The MOLP model involves the simultaneous maximization of three linear objective functions associated with three criteria, which are social, technological, and economic criterion. This model is different from the traditional one which only involves the maximization of economic criterion. The presented problem in this model can be formulated as a problem of optimizing a linear function over an efficient set of MOLP. Its application to the National R&D Project in I&T Industry is also presented. In this application, the Analytic Hierarchy Process (AHP) is proposed to estimate the weights, which are used as the coefficients in each objective function of the MOLP model and in a linear decision function. By solving this problem, it yields a suitable R&D investment ratio to each technology field. It is showed that the MOLP model can be useful decision aid in formulating R&D investment plan in I&T industry which needs to be decided by group decision makers, not by an individual. It is expected that the MOLP model works as the basis for planning R&D investment strategy in I&T industry.

• 한국전자통신학회논문지
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• 제17권1호
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• pp.161-166
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• 2022

본 논문에서는 데이터 분석 도구인 R을 이용하여 빅데이터 분석을 수행할 때 발생하는 문제점을 분석하고, 빅데이터의 분산 처리를 효과적으로 지원하는 스파크와 R을 연계한 SparkR을 이용한 분석의 유용성을 제시하고자 한다. 먼저, 대량의 데이터를 로딩하고 연산을 수행할 때 발생하는 R의 메모리 할당 문제점과 R과 비교한 SparkR의 특징 및 프로그래밍 환경을 분석한다. 그리고, 선형 회귀 분석을 각각의 환경에서 수행할 때의 실행 성능을 비교 분석한다. 분석 결과 SparkR을 통해 추가적인 언어 학습 없이도 R을 그대로 이용하여 데이터 분석에 활용할 수 있음을 보였으며, SparkR을 이용하여 R로 작성된 코드를 클러스터 내 노드 수의 증가에 따라 효과적으로 분산 처리할 수 있었다.