• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2014.10a
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• pp.53-55
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• 2014

Offshore 에서의 oil & gas 생산은 해상이라는 환경으로 인한 고유의 특성 때문에 항상 다수의 변수들에 영향을 받으며, 막대한 비용이 소요되기 때문에 비용을 최소화하며, 비용 대비 수익을 최대화시키기 위한 optimal design이 필수이다. 본 논문은 가상의 offshore plant와 이에서 생산된 oil의 수요지들을 설정하여 시장수요에 따른 offshore 생산의 최적화 문제를 연구대상으로 하며, 다수의 offshore oil fields를 보유한 major oil company가 당면할 수 있는 offshore production에 관한 문제를 일반화하여 정의하고, 이윤을 극대화시킬 수 있는 최적화 모형을 혼합정수계획모형(mixed integer programming)으로 정식화 하였다. 최적화 모형의 해는 Microsoft office excel solver를 통해 구하였으며 그 계산실험의 결과를 요약하여 보고한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2002.04b
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• pp.1187-1190
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• 2002

휴대폰 사용 인구가 급증하고, 최근 출시되는 휴대폰의 사양이 좋아짐에 따라, 휴대폰을 위한 응용프로그램(application program) 개발자 역시 늘어나고 있다. 하지만, 휴대폰이 PC 에 비해 제한된 자원을 갖는 장치이기 때문에, 고성능의 PC 에서는 고려하지 않았던 최적화 문제가 발생하고 이를 해결해야 할 필요가 있다. 더욱이 최근에는 휴대폰으로 동영상을 보려는 시도가 늘고있는데, 동영상 플레이어는 기타 대부분의 응용 프로그램보다 많은 연산이 필요한 응용 프로그램이므로 최적화 문제가 더욱 절실해졌다. 본 논문에서는 휴대폰에서 특히, BREW platform 에서 프로그래밍 시에 필요한 최적화 기법을 소개한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2018.05a
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• pp.442-444
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• 2018

본 논문에서는 GA(Genetic Algorithm) 기반 점증적 입자모델(IGM: Incremental Granular Model)의 최적화 설계를 제안한다. IGM의 성능은 다양한 실세계 응용예제를 통해 성공적으로 연구되어져왔다. 그러나, IGM의 문제로 각 컨텍스트에서 동일한 클러스터 수가 사용되는 점과 전형적인 퍼지화 계수가 설정된다는 점이 있다. 이러한 문제를 해결하기 위해 IGM을 최적화하여 각 컨텍스트에서 클러스터 중심의 수와 퍼지화 계수를 최적화하는 설계 방법을 제시했다. 제안된 방법의 타당성을 확인하기 위해 Ecotect에서 시뮬레이션 한 12가지 건물 형태를 사용하여 에너지 효율 예측에 대한 실험을 수행하였고, 제안된 방법은 기존의 IGM보다 우수한 성능을 보이는 것을 확인했다.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.241-243
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• 2023

양자컴퓨터의 발전이 빠르게 진행됨에 따라서 고전컴퓨터에서는 해결하지 못하는 문제에 대하여 양자 알고리즘을 활용하여 해결하고자 하는 연구가 진행되고 있다. 이중 소인수 분해 및 이산로 그 문제 해결이 가능한 Shor's Algorithm 및 이에 대한 공개키 암호 해독을 위한 양자 자원량 분석에 대한 연구가 진행되고 있다. 하지만 양자 컴퓨터의 가용 양자 자원량이 제한적이라는 점과, 시간적인 측면에서의 최적화는 암호의 보안강도에 영향을 끼치기 때문에 알고리즘 최적화 연구가 필요하다. 따라서 본 논문에서는 암호를 대상으로 한 Shor's Algorithm 양자 회로의 최적화 동향을 조사하고 향후 연구 방향에 대해서 기술한다.

• Journal of the Korea Society for Simulation
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• v.27 no.2
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• pp.83-90
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• 2018

This paper describes the method of hull shape optimization to improve the resistance performance of planing hulls when a reference hull shape and its principal dimensions are given. First, the planing hull of precedent research is adopted as the reference hull and an optimization problem is formulated by defining hull shape parameters. The search space of this research is discretized for computing cost and DPSO(Discrete binary version of Particle Swarm Optimization) method is used to solve the optimization problem. As the result of optimization, the decrease of resistance is confirmed from the comparison between the reference hull's and the modified hull's planing performance from computational results.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.8
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• pp.917-920
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• 2016

SpSF algorithm is direction-of-arrival estimation algorithm based on sparse representation of incident signlas. Cost function to be optimized for DOA estimation is multi-dimensional nonlinear function, which is hard to handle for optimization. After some manipulation, the problem can be cast into convex optimiztion problem. Convex optimization problem tuns out to be constrained optimization problem, where the parameter in the constraint has to be determined. The solution of the convex optimization problem is dependent on the specific parameter value in the constraint. In this paper, we propose a rule-of-thumb for determining the parameter value in the constraint. Based on the fact that the noise in the array elements is complex Gaussian distributed with zero mean, the average of the Frobenius norm of the matrix in the constraint can be rigorously derived. The parameter in the constrint is set to be two times the average of the Frobenius norm of the matrix in the constraint. It is shown that the SpSF algorithm actually works with the parameter value set by the method proposed in this paper.

• Journal of Internet Computing and Services
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• v.5 no.4
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• pp.53-62
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• 2004

This paper presents a study on the optimization for brokering between cargos and ships for future e-logistics. The primary contribution of this research is that we establish an optimization model by formalizing the criteria for the brokering such as time constraints, weight constraints, and preference values between cargos and ships. Another important contribution is that we not only investigate the complexity and the tractability of the optimal brokering problem but present how to evaluate the performance of the optimization program through an experiment. We first derive the preference values between cargos and ships using the time and the weight constraints. These preference values between each pair of cargos and ships are assigned to corresponding binary decision variables as coefficients in the objective function. The optimization model selects pairs of cargos and ships in a way that the sum of the preference values is maximized while satisfying given constraints. Experiment shows that the Davis-Putnam based optimization program finds optimal solutions in reasonable time for the problems with less than 90 decision variables.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.2
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• pp.255-262
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• 2015

In the absence of a deterministic algorithm for economic load dispatch optimization problem (ELDOP), existing algorithms proposed as solutions are inevitably non-deterministic heuristic algorithms. This paper, therefore, proposes a balance-and-swap algorithm to solve an ELDOP. Firstly, it balances the initial value to ${\Sigma}P_i=P_d$ by subsequently reducing power generation for each adult-step and baby-step and selects the minimum cost-generating method. Subsequently, it selects afresh the minimum cost-generating method after an optimization of the previously selected value with adult-step baby-step swap and giant-step swap methods. Finally, we perform the $P_i{\pm}{\beta}$, (${\beta}=0.1,0.01,0.001,0.0001$) swap. When applied to the 3 most prevalently used economic load dispatch problem data, the proposed algorithm has obtained improved results for two and a result identical to the existing one for the rest. This algorithm thus could be applied to ELDOP for it has proven to consistently yield identical results and to be applicable to all types of data.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.8
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• pp.3-9
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• 2015

Under the maximum transmit power constraint and the minimum rate constraint, we propose the optimal number of transmit antennas and transmit power which maximize energy-efficiency (EE) in multi-user multiple-input multiple-output (MIMO) downlink system with the maximal ratio transmission (MRT) precoding. Because the optimization problem for the instantaneous channel is difficult to solve, we use independence of individual channel, average channel gain and path loss to approximate the objective function. Since the approximated EE optimization problem is two-dimensional search problem, we find the optimal number of transmit antennas and transmit power using Lagrange multipliers and our proposed algorithm. Simulation results show that the number of transmit antennas and power obtained by proposed algorithm are almost identical to the value by the exhaustive search.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.45 no.8
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• pp.662-670
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• 2017

This paper proposes an optimization-based procedure to determine the parameters of the Apollo guidance law for Korean lunar lander mission. A lunar landing mission is formulated as a trajectory optimization problem to minimize the fuel consumption and the reference trajectory for the lander is obtained by solving the problem in the pre-flight phase. Some parameters of the Apollo guidance, which are coefficients of the polynomial used to define the guidance command, are selected based on the reference trajectory obtained in the pre-flight phase. A case study for the landing guidance of Korean lunar lander mission using the proposed procedure is conducted to demonstrate its effectiveness.