• Transactions of the Korean Society of Automotive Engineers
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• v.4 no.4
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• pp.190-200
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• 1996

Step-by-step time integration methods are widely used for solving structural dynamics problem. One difficult yet critical choice an analyst must make is to decide an appropriate time step size. The choice of time step size has a significant effect on solution accuracy and computational expense. The objective of this research is to derive error estimate for newly developed time integration method and develop automatic time step size control algorithm for structural dynamics. A formula for computing error tolerance is derived based on desired period resolution. An automatic time step size control strategy is proposed based on a normalized local error estimate for the generalized-α method. Numerical examples demonstrate the developed strategy satisfies general design criteria for time step size control algorithm for dynamic problem.

• Transactions of the Korean Society of Automotive Engineers
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• v.4 no.1
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• pp.110-122
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• 1996

The objective of this study is to understand the dynamic characterictics of OHV type valve trains and to design and optimal cam profile which will improve engine performance. A numerical model for valve train dynamics is presented, which aims at both accuracy and computational efficiency. The lumped mass model and distributed parameter model were used to describe the valve train dynamics. Nonlinear characterictics in the valve spring behavior were included in the model. Comprehensive experiments were carried out concerning the valve train dynamics, and the model was tuned based on the test results. The dynamic model was used in designing an optimal cam profile. Because the objective function has many local minima, a conventional local optimizer cannot be used to find an optimal solution. A modified adaptive random search method is successfully employed to solve the problem. Cam lobe area could be increased up to 7.3% without any penalties in kinematic and dynamic behaviors of the valve train.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.12B
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• pp.1468-1473
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• 2011

With the proliferation of wireless LAN and smart phones, IP local broadcasting technology has been developed, and the new solution should be studied for error corrupted frames in the wireless broadcasting channel. In push service system using point-to-multi-point connection among broadcasting server and receivers, the technology proposed in this paper provides an effective data broadcasting system by employing frame length adjustment, redundant transmission, and repetitive transmission method.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.50 no.11
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• pp.520-527
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• 2001

This paper suggests a new methodology of evolutionary computations - an Adaptive Evolutionary Algorithm (AEA) for solving the Economic Load Dispatch (ELD) problem which has piecewise quadratic cost functions and prohibited operating zones with many local minima. AEA uses a genetic algorithm (GA) and an evolution strategy (ES) in an adaptive manner in order to take merits of two different evolutionary computations: global search capability of GA and local search capability of ES. In the reproduction procedure, proportions of the population by GA and the population by ES are adaptively modulated according to the fitness. Case studies illustrate the superiority of the proposed methods to existing conventional methods in power generation cost and computation time. The results demonstrate that the AEA can be applied successfully in the solution of ELD with piecewise quadratic cost functions and prohibited operating zones

• Smart Structures and Systems
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• v.7 no.3
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• pp.199-211
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• 2011

Using computational modeling, we design a pair of biomimetic microcapsules that exploit chemical mechanisms to communicate and alter their local environment. As a result, these synthetic objects can undergo autonomous, directed motion. In the simulations, signaling microcapsules release "agonist" particles, while target microcapsules release "antagonist" particles and the permeabilities of both capsule types depend on the local particle concentration in the surrounding solution. Additionally, the released nanoscopic particles can bind to the underlying substrate and thereby create adhesion gradients that propel the microcapsules to move. Hydrodynamic interactions and the feedback mechanism provided by the dissolved particles are both necessary to achieve the cooperative behavior exhibited by these microcapsules. Our model provides a platform for integrating both the spatial and temporal behavior of assemblies of "artificial cells", and allows us to design a rich variety of structures capable of exhibiting complex dynamics. Due to the cell-like attributes of polymeric microcapsules and polymersomes, material systems are available for realizing our predictions.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.26 no.1
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• pp.85-94
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• 2003

In this paper, a mathematical model is developed for economic design of multi-stage distribution system that consists of factory, central distribution centers, local distribution centers and retailers. The retailers are supplied products from different stage suppliers according to order size. The retailers are supplied products from factory if demand amount is large, central distribution center if medium, local distribution center if small. The economic design is to determine the economic size of facility factors that consist of distribution system. The cost factors are transportation cost from supply places to demand places, handling cost at distribution centers and inventory holding cost at retailers. It is to determine the transportation route of each retailer, the size and number of the vehicle at factory and distribution centers, the handling amount at distribution centers in order to minimize the total costs. The mathematical model is represented, the solution procedure is developed, and a numerical example is shown.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2002.05a
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• pp.979-986
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• 2002

Constraint Programming is an appealing technology for modeling and solving various real-world problems. and metaheuristic is the most successful technique available for solving large real-world vehicle routing problems. Constraint Programming and metaheuristic are complementary to each other. This paper describes how iterative improvement techniques can be used in a Constraint Programming framework(LOG Solver and ILOG Dispatcher) for Vehicle Routing Problem. As local search gets trapped in local solution, the improvement techniques are used in conjunction with metaheuristic method.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.5 no.4
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• pp.281-285
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• 2005

Learning and evolving are two basics for data mining. As compared with classical learning theory based on objective function with minimizing training errors, the recently evolutionary computing has had an efficient approach for constructing optimal model without the minimizing training errors. The global search of evolutionary computing in solution space can settle the local optima problems of learning models. In this research, combining co-evolving algorithm into statistical learning theory, we propose an co-evolutionary computing for statistical learning theory for overcoming local optima problems of statistical learning theory. We apply proposed model to classification and prediction problems of the learning. In the experimental results, we verify the improved performance of our model using the data sets from UCI machine learning repository and KDD Cup 2000.

• Journal of the Korea Safety Management & Science
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• v.10 no.1
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• pp.145-153
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• 2008

The vehicle routing problem determines each vehicle routes to find the transportation costs, subject to meeting the customer demands of all delivery points in geography. Vehicle routing problem is known to be NP-hard, and it needs a lot of computing time to get the optimal solution, so that heuristics are more frequently developed than optimal algorithms. This study aims to develop a heuristic method which combines guided local search with a tabu search in order to minimize the transportation costs for the vehicle routing assignment and uses ILOG programming library to solve. The computational tests were performed using the benchmark problems. And computational experiments on these instances show that the proposed heuristic yields better results than the simple tabu search does.

• International Journal of Control, Automation, and Systems
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• v.4 no.5
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• pp.575-591
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• 2006

In a previous research, we presented the Grid Method and confirmed it as a systematic and efficient problem formulation method for the task-oriented design of robot kinematics. However, our previous research was limited in two ways. First, it gave only a local optimum due to its use of a local optimization technique. Second, it used constant weights for a cost function chosen by the manual weights tuning algorithm, thereby showing low efficiency in finding an optimal solution. To overcome these two limitations, therefore, this paper presents a global optimization technique and an adaptive weights tuning algorithm to solve a formulated problem using the Grid Method. The efficiencies of the proposed algorithms have been confirmed through the kinematic design examples of various robot manipulators.