• 정보처리학회논문지A
• /
• 제8A권1호
• /
• pp.48-55
• /
• 2001

Using BDD, we can represent Boolean functions uniquely and compactly, Hence, BDD have become widely used for CAD applications, such as logic synthesis, formal verification, and etc. The size of the BDD representation for a function is very sensitive to the choice of orderings on the input variables. Therefore, it is very important to find a good variable ordering which minimize the size of the BDD. Since finding an optimal ordering is NP-complete, several heuristic algorithms have been proposed to find good variable orderings. In this paper, we propose a variable ordering algorithm based on the $\mu$O(microcanonical optimization). $\mu$O consists of two distinct procedures that are alternately applied : Initialization and Sampling. The initialization phase is to executes a fast local search, the sampling phase leaves the local optimum obtained in the previous initialization while remaining close to that area of search space. The proposed algorithm has been experimented on well known benchmark circuits and shows superior performance compared to a algorithm based on simulated annealing.

• 산업경영시스템학회지
• /
• 제21권46호
• /
• pp.33-49
• /
• 1998

In order to improve the performance of relational databases, one has to reduce the number of disk accesses necessary to transfer data from disk to main memory. The paper proposes to reduce the number of disk I/O accesses by vertically partitioning relation into fragments and allowing attribute replication to fragments if necessary. When zero-one integer programming model is solved by the branch-and-bound method, it requires much computing time to solve a large sized problem. Therefore, heuristic solutions using genetic algorithm(GA) are presented. GA in this paper adapts a few ideas which are different from traditional genetic algorithms, for examples, a rank-based sharing fitness function, elitism and so on. In order to improve performance of GA, a set of optimal parameter levels is determined by the experiment and makes use of it. As relations are vertically partitioned allowing attribute replications and saved in disk, an attribute replicating vertical partition method by GA can attain less access cost than non-attribute-replication one and require less computing time than the branch-and-bound method in large-sized problems. Also, it can acquire a good solution similar to the optimum solution in small-sized problem.

• 대한산업공학회지
• /
• 제39권4호
• /
• pp.253-259
• /
• 2013

Investment scenarios in the transportation network design problem usually contain installation or expansion of multi-mode transportation links. When one applies the mode choice analysis and traffic assignment sequentially for each investment scenario, it is possible that the travel impedance used in the mode choice analysis is different from the user equilibrium cost of the traffic assignment step. Therefore, to estimate the travel impedance and mode choice accurately, one needs to develop a combined model for the mode choice and traffic assignment. In this paper, we derive the inverse demand and the excess demand functions for the multi-mode multinomial logit mode choice function and develop a combined model for the multi-mode variable demand traffic assignment problem. Using data from the regional O/D and network data provided by the KTDB, we compared the performance of the partial linearization algorithm with the Frank-Wolfe algorithm applied to the excess demand model and with the sequential heuristic procedures.

• Journal of information and communication convergence engineering
• /
• 제9권4호
• /
• pp.379-384
• /
• 2011

The scope of the problems that could be solved by monitoring and the improvement of the recognition time is directly correlated to the performance of the management function of the business process. However, the current monitoring process of business activities decides whether to apply warnings or not by assuming a fixed environment and showing expressions based on the design rules. Also, warnings are applied by carrying out the measuring process when the event attribute values are inserted at every point. Therefore, there is a limit for distinguishing the range of occurrence and the level of severity in regard to the new external problems occurring in a complicated environment. Such problems cannot be ed. Also, since it is difficult to expand the range of problems which can be possibly evaluated, it is impossible to evaluate any unexpected situation which could occur in the execution period. In this paper, a process-evaluating model based on the goal scenario is suggested to provide constant services through the current monitoring process in regard to the service demands of the new scenario which occurs outside. The new demands based on the outside situation are analyzed according to the goal scenario for the process activities. Also, by using the meta-heuristic algorithm, a similar process model is found and identified by combining similarity and interrelationship. The process can be stopped in advance or adjusted to the wanted direction.

• 스마트미디어저널
• /
• 제7권3호
• /
• pp.9-15
• /
• 2018

본 논문에서는 음성존재확률을 이용하여 다채널 위너필터의 이득을 최적으로 변형하는 방법을 제안한다. 기존의 음성존재확률을 이용한 다채널 위너필터의 변형은 다소 경험적인 방법을 사용하기 때문에 잔여잡음의 양을 줄이면 음성왜곡이 증가하는 문제가 있다. 하지만, 제안된 최적 변형 다채널 위너필터는 음성존재확률을 최적 필터를 도출하기 위한 비용함수에 적용하여 비제한적 최소화 문제의 해를 이용하여 잔여잡음의 양과 음성왜곡을 동시에 줄일 수 있는 결과를 보였다. 잡음제거된 파형과 스펙트로그램의 평가를 통해서 제안된 최적 변형 다채널 위너필터가 종래의 다채널 위너필터와 비교하여 향상된 SNR과 음성왜곡을 나타냄을 확인할 수 있었다.

• 한국음향학회지
• /
• 제38권5호
• /
• pp.511-521
• /
• 2019

본 연구에서는 무한 유체에 놓여있는 유한 길이의 탄성 원통 쉘에 외부에서 비스듬히 평면파가 입사할 때 발생하는 음향 산란 현상을 이론적으로 연구했다. 유한 길이의 원통 쉘에서는 해석적인 산란 해가 존재하지 않기 때문에, Kirchhoff 가정을 적용한 Ye의 산란 기법[Z. Ye, J. Acoust. Soc. Am. 102, 877-884 (1997)]을 사용했다. 탄성 원통 쉘의 특성은 3차원 탄성파 이론을 적용하여 구현했으며 원통 쉘 내부의 유체를 고려했다. 유도된 해석 해를 이용하여 내부 유체가 산란 음장에 미치는 효과, Rayleigh 변수에 대한 산란 음장, 탄성 재질의 변화에 따른 먼 거리 산란 함수를 살펴보았다.

• 한국항공우주학회지
• /
• 제47권8호
• /
• pp.590-598
• /
• 2019

현대 사회에서 인공위성은 통신, 영상 등의 분야에서 널리 이용되고 있다. 이 중에서도 인공위성을 통해 획득한 영상은 넓은 지역에 대한 다양한 정보를 담고 있어 농업, 자원개발 및 활용, 군사적 목적 등으로 활용되고 있다. 인공위성의 특성상 영상을 획득할 수 있는 시간이 매우 제한적이므로 주어진 시간 내에 최대한 효율적인 영상획득을 수행하는 것이 중요하다. 이를 위해서 본 연구에서는 인공위성이 영상을 획득하는 데 소요되는 시간 및 자세 기동에 대한 모델링을 수행하고 이를 바탕으로 휴리스틱 평가함수를 이용한 임무설계 알고리즘을 제안하고 수치 시뮬레이션을 통하여 해당 알고리즘의 성능을 검증하였다.

• Geomechanics and Engineering
• /
• 제24권3호
• /
• pp.237-251
• /
• 2021

The main purpose of this study is to investigate the performance of the proposed hybrid teaching-learning based optimization algorithm on the optimum design of reinforced concrete (RC) cantilever retaining walls. For this purpose, three different design examples are optimized with 100 independent runs considering continuous and discrete variables. In order to determine the algorithm performance, the optimization results were compared with the outcomes of the nine powerful meta-heuristic algorithms applied to this problem, previously: the big bang-big crunch (BB-BC), the biogeography based optimization (BBO), the flower pollination (FPA), the grey wolf optimization (GWO), the harmony search (HS), the particle swarm optimization (PSO), the teaching-learning based optimization (TLBO), the jaya (JA), and Rao-3 algorithms. Moreover, Rao-1 and Rao-2 algorithms are applied to this design problem for the first time. The objective function is defined as minimizing the total material and labor costs including concrete, steel, and formwork per unit length of the cantilever retaining walls subjected to the requirements of the American Concrete Institute (ACI 318-05). Furthermore, the effects of peak ground acceleration value on minimum total cost is investigated using various stem height, surcharge loads, and backfill slope angle. Finally, the most robust results were obtained by HTLBO with 50 populations. Consequently the optimization results show that, depending on the increase in PGA value, the optimum cost of RC cantilever retaining walls increases smoothly with the stem height but increases rapidly with the surcharge loads and backfill slope angle.

• 한국항공우주학회지
• /
• 제49권7호
• /
• pp.581-588
• /
• 2021

본 논문은 전투기 레이다 공대공, 공대지 동시 운용 모드에서의 빔 스케줄링 방법을 다룬다. 양질의 전장 상황 인식을 위해 임무들의 우선순위와 더불어 공대공, 공대지 탐색 임무가 교차로 수행되어야 한다는 요구조건을 정립하였다. 그리고 이를 만족하기 위해 WMDD를 개선한 실시간 휴리스틱 빔 스케줄링 방법을 제안한다. 제안된 스케줄링 방법은 실제 레이다 임무 처리 메커니즘 및 측정 모델이 구현된 시뮬레이션 환경에서 비교 분석하였으며 임무 지연시간 관점에서의 성능 향상을 확인하였다.

• Advances in Computational Design
• /
• 제7권1호
• /
• pp.1-17
• /
• 2022

In this study, a new strategy is presented to transmit the fundamental elastic beam problem into the modern optimization platform and solve it by using artificial intelligence (AI) tools. As a practical example, deflection of Euler-Bernoulli beam is mathematically formulated by 2nd-order ordinary differential equations (ODEs) in accordance to the classical beam theory. This fundamental engineer problem is then transmitted from classic formulation to its artificial-intelligence presentation where the behavior of the beam is simulated by using neural networks (NNs). The supervised training strategy is employed in the developed NNs implemented in the heuristic optimization algorithms as the fitness function. Different evolutionary optimization tools such as genetic algorithm (GA) and particle swarm optimization (PSO) are used to solve this non-linear optimization problem. The step-by-step procedure of the proposed method is presented in the form of a practical flowchart. The results indicate that the proposed method of using AI toolsin solving beam ODEs can efficiently lead to accurate solutions with low computational costs, and should prove useful to solve more complex practical applications.