• 한국정보통신학회:학술대회논문집
• /
• 한국해양정보통신학회 2002년도 추계종합학술대회
• /
• pp.251-254
• /
• 2002

이동 무선 통신 시스템을 설계할 때 기지국(BTS), 기지국 콘트롤러(BSC), 이동 교환국(MSC)의 위치는 매우 중요한 파라미터 중 하나이다. 무선 통신 시스템을 설계할 때 여러 가지 복잡한 변수들을 잘 조합하여 비용이 최소가 되도록 설계해야 한다. 이러한 문제를 해결하는데 필요한 알고리즘이 전역 최적화 알고리즘이며, 지금까지 전역 최적화 검색 기술로 Random Walk, Simulated Annealing, Tabu Search, Genetic Algorithm과 같은 조합 최적화 기술이 사용되어 왔다. 본 논문은 이동 통신 시스템의 기지국, 기지국 콘트롤러, 이동 교환국의 위치 최적화에 위의 4가지 알고리듬들을 적용하여 각 알고리듬의 결과를 비교 분석하며 알고리듬에 의한 최적화 과정을 보여 준다.

• 한국콘텐츠학회논문지
• /
• 제11권3호
• /
• pp.100-107
• /
• 2011

휴리스틱 탐색에서 강화(Intensification)와 다양화(Diversification)의 조화는 중요한 연구 부분이다. 본 논문에서는 개미 집단 최적화(Ant Colony Optimization, ACO) 접근법의 하나인 개미 집단 시스템(Ant Colony System, ACS)에서 강화와 다양화의 조화를 통한 성능 향상시키는 방법을 제안한다. 제안 방법은 다양화 전략으로 전역 최적 경로가 향상되지 않는 경우 반복 탐색 구간을 고려해 상태전이 규칙의 파라미터를 변경해 탐색하고, 이러한 다양화 전략을 통해 발견된 전역 최적 경로에서 이전 전역 최적 경로와 현재 전역 최적 경로의 중복 간선에 대해 페로몬을 강화시켜 탐색하는 혼합된 탐색 방법을 제안한다. 그리고, 실험을 통해 제안된 방법이 기존 ACS-3-opt 알고리즘, ACS-Subpath 알고리즘, ACS-Iter 알고리즘, ACS-Global-Ovelap 알고리즘에 비해 최적 경로 탐색 및 평균 최적 경로 탐색의 성능이 우수함을 보여 준다.

• 대한기계학회논문집A
• /
• 제30권7호
• /
• pp.841-848
• /
• 2006

Many researchers are developing computational prediction methods for protein tertiary structures to get much more information of protein. These methods are very attractive on the aspects of breaking technologies of computer hardware and simulation software. One of the computational methods for the prediction is a fragment assembly method which shows good ab initio predictions at several cases. There are many barriers, however, in conventional fragment assembly methods. Argues on protein energy functions and global optimization to predict the structures are in progress fer example. In this study, a new prediction method for protein structures is proposed. The proposed method mainly consists of two parts. The first one is a fragment assembly which uses very shot fragments of representative proteins and produces a prototype of a given sequence query of amino acids. The second one is a global optimization which folds the prototype and makes the only protein structure. The goodness of the proposed method is shown through numerical experiments.

• 한국항해항만학회지
• /
• 제30권2호
• /
• pp.137-143
• /
• 2006

The optimum grillage design belongs to nonlinear constrained optimization problem. The determination of beam scantlings for the grillage structure is a very crucial matter out of whole structural design process. The performance of optimization methods, based on penalty functions, is highly problem-dependent and many methods require additional tuning of some variables. This additional tuning is the influences of penalty coefficient, which depend strongly on the degree of constraint violation. Moreover, Binary-coded Genetic Algorithm (BGA) meets certain difficulties when dealing with continuous and/or discrete search spaces with large dimensions. With the above reasons, Real-coded Micro-Genetic Algorithm ($R{\mu}GA$) is proposed to find the optimum beam scantlings of the grillage structure without handling any of penalty functions. $R{\mu}GA$ can help in avoiding the premature convergence and search for global solution-spaces, because of its wide spread applicability, global perspective and inherent parallelism. Direct stiffness method is used as a numerical tool for the grillage analysis. In optimization study to find minimum weight, sensitivity study is carried out with varying beam configurations. From the simulation results, it has been concluded that the proposed $R{\mu}GA$ is an effective optimization tool for solving continuous and/or discrete nonlinear real-world optimization problems.

• 한국정보과학회:학술대회논문집
• /
• 한국정보과학회 2004년도 가을 학술발표논문집 Vol.31 No.2 (2)
• /
• pp.700-702
• /
• 2004

A local-step optimization method is proposed to supplement the global-step optimization methods which adopt online update mode of internal weights and error energy as stop criterion in learning of multilayer perceptrons (MLPs). This optimization method is applied to the standard online error backpropagation(EBP) and the performance is evaluated for a speaker verification system.

• Journal of applied mathematics & informatics
• /
• 제26권1_2호
• /
• pp.283-290
• /
• 2008

This paper is motivated by the problem of fitting a group of cuboids into a simplified rotating vessel of the artificial satellite. Here we introduce a combinatorial optimization model which reduces the three-dimensional layout problem with behavioral constraints to a finite enumeration scheme. Moreover, a global combinatorial optimization algorithm is described in detail, which is an improved graph-theoretic heuristic.

• Journal of applied mathematics & informatics
• /
• 제5권3호
• /
• pp.701-716
• /
• 1998

In this paper we develop algorithms in programming lan-guage SCHEME for implementation of the main first order gradient techniques for unconstrained optimization. Implementation of the de-scent techniques which use non-optimal descent steps as well as imple-mentation of the optimal descent techniques are described. Also we investigate implementation of the global problem called optimization along a line. Developed programs are effective and simpler with re-spect to the corresponding in the procedural programming languages. Several numerical examples are reported.

• 전자공학회논문지A
• /
• 제29A권4호
• /
• pp.64-73
• /
• 1992

This paper presents the design of multi-level logic optimization algorithm and the development of the SMILE system based on the algorithm. Considering the fanin constraints in algorithmic level, SMILE performs global and local optimization in a predefined sequence using heuristic information. Designed under the Sogang Silicon Compiler design environment, SMILE takes the SLIF netlist or Berkeley equation formats obtained from high-level synthesis process, and generates the optimized circuits in the same format. Experimental results show that SMILE produces the promising results for some circuits from MCNC benchmarks, comparable to the popularly used multi-level logic optimization system, MIS.

• 한국전산구조공학회:학술대회논문집
• /
• 한국전산구조공학회 2002년도 봄 학술발표회 논문집
• /
• pp.225-232
• /
• 2002

Simple genetic algorithm(SGA) has been used to optimize a lot of structural optimization problems because it can optimize non-linear problems and obtain the global solution. But, because of large evolving populations during many generations, it takes a long time to calculate fitness. Therefore this paper applied micro-genetic algorithm(μ -GA) to structural optimization and compared results of μ -GA with results of SGA. Additionally, the Paper applied μ -GA to gate optimization problem for injection molds by using simulation program CAPA.

• International Journal of Aeronautical and Space Sciences
• /
• 제18권4호
• /
• pp.780-787
• /
• 2017

The propellant grain configuration is a design variable that determines the shape and performance of a solid rocket motor. Grain configuration variables have complicated effects on the motor performance; so the global optimization problem has to be solved in order to design the configuration variables. The grain performance has been analyzed by means of the grain burn-back and internal ballistic analysis, and the optimization technique searches for the configuration variables that satisfy the requirements. The deterministic and stochastic optimization techniques have been applied for the grain optimization, but the results are imperfect. In this study, the optimization design of the configuration variables has been performed using the hybrid optimization technique, which combines those two techniques. As a result, the hybrid optimization technique has proved to be efficient for the grain optimization design.