• The KIPS Transactions:PartA
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• v.8A no.1
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• pp.48-55
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• 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.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.21 no.46
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• pp.33-49
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• 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.

• Journal of Korean Institute of Industrial Engineers
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• v.39 no.4
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• pp.253-259
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• 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
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• v.9 no.4
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• pp.379-384
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• 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.

• Smart Media Journal
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• v.7 no.3
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• pp.9-15
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• 2018

This paper proposes an optimal gain modification method of the Multichannel Wiener filter (MWF) using speech presence probabilities. Conventional gain modification methods of MWFs have the problem of the increase of speech distortions while reducing residual noises with its relative heuristic approach. However, the proposed optimal gain modification method, derived by solving the unconstrained minimization problem of the probability-involved cost function, reduces amounts of residual noises and signal distortions simultaneously. Through an evaluation of the filtered waveforms and spectrograms, it is verified that the proposed method results in an improved SNR with less signal distortions compared to the conventional MWF.

• The Journal of the Acoustical Society of Korea
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• v.38 no.5
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• pp.511-521
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• 2019

In this study, we theoretically study the acoustic scattering of an obliquely incident plane wave from a finite elastic cylindrical shell. A heuristic scattering method of Ye [Z. Ye, J. Acoust. Soc. Am. 102, 877-884 (1997)] for a finite fluid cylinder is extended into a finite elastic cylindrical shell since no analytic solutions exist in the finite cylinder. The elastic cylindrical shell is modeled with the 3D elastic wave theory considering internal fluid. Using the derived analytic solution, we observe the effect of the internal fluid on the scattering field, the scattering field for the Rayleigh parameter, and the far-field scattering function for the elastic property of the cylindrical shell.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.47 no.8
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• pp.590-598
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• 2019

Today, satellites are widely used in many fields like communication and image recoding. The image acquired by satellites contains variety information of wide region. Therefore, they are used for agriculture, resource exploitation and management, and military purpose. The satellite is required to acquire images effectively in a given time period. Because the period that satellites can acquire images is very restrictive. In this study, the modeling of processing time and attitude maneuvering for satellite image acquisition is performed. From this modeling, mission planning algorithm using heuristic evaluation function is suggested and performance of the proposed algorithm is verified by numerical simulation.

• Geomechanics and Engineering
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• v.24 no.3
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• pp.237-251
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• 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.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.49 no.7
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• pp.581-588
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• 2021

This paper deals with a beam scheduling method in fighter interleaving mode. Not only the priority of tasks but also operational requirements that air-to-ground and air-to-air search tasks should be executed alternatively are established to maximize high-quality of situational awareness. We propose a real-time heuristic beam scheduling method that is advanced from WMDD to satisfies the requirements. The proposed scheduling method is implemented in a simulation environment resembling the task processing mechanism and measurement model of a radar. Performance improvement in terms of task delay time is observed.

• Advances in Computational Design
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• v.7 no.1
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• pp.1-17
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• 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.