• Bulletin of the Korean Chemical Society
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• v.23 no.9
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• pp.1267-1271
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• 2002

The conformation dependences of basis set superposition errors (BSSE) for 1,2-difluoroethane (DFE) and 1,2-dimethoxyethane (DME) molecules have been estimated using counterpoise method at the Moller-Plesset second order perturbation (MP2) level of theory with various basis sets, assuming that all BSSE dependences on conformations are due to the change in CC bond. The BSSE on the energy differences between eclipsed and gauche forms of DFE are in the range of 0.2-1.2 kcal/mol and those between local minima, gauche and anti forms, are less than 0.2 kcal/mol. For the larger DME molecule, the BSSE differences between local minima are still less than 0.4 kcal/mol, but may not be ignored compared to the energy differences of 0.2-3.0 kcal/mol between conformers.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.14-17
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• 1995

Various methods and techniques have been proposed for solving optimization problems; the methods have been applied to various practical problems. However the methods have demerits. The demerits which should be covered are, for example, falling into local minima, or, a slow convergence speed to optimal points. In this paper, Likelihood Search Method (L.S.M.) is proposed for searching for a global optimum systematically and effectively in a single framework, which is not a combination of different methods. The L.S.M. is a sort of a random search method (R.S.M.) and thus can get out of local minima. However exploitation of gradient information makes the L.S.M. superior in convergence speed to the commonly used R.S.M..

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.7
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• pp.624-630
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• 2007

The dynamic window approach(DWA) is a well known technique for reactive collision avoidance. It shows safe and efficient performance in real-world experiments. However, a robot can get stuck in local minima because no information about the connectivity of the free space is used to determine the motion. The global DWA can solve this problem of local minima by adding a navigation function. Even with the global DWA, it is still difficult for a robot to execute an abrupt change in its direction, for example, entering from the corridor to a doorway. This paper proposes a modified global DWA using the included angles of waypoints extracted from an optimal path. This scheme enables the robot to decelerate in advance before turning into the doorway. Therefore the robot can reach the goal position more safely and efficiently at high speeds.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.278-278
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• 2000

In this paper, we introduce a new genetic reordering operator based on the concept of schema to solve optimization problems such as the Traveling Salesman Problem(TSP) and maximizing or minimizing functions. In particular, because TSP is a well-known combinational optimization problem andbelongs to a NP-complete problem, there is huge solution space to be searched. For robustness to local minima, the operator separates selected strings into two parts to reduce the destructive probability of good building blocks. And it applies inversion to the schema part to prevent the premature convergence. At the same time, it searches new spaces of solutions. Additionally, the non-schema part is applied to inversion for robustness to local minima. By doing so, we can preserve diversity of the distributions in population and make GA be adaptive to the dynamic environment.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.8
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• pp.50-59
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• 1996

In this paper, a new hierarchical motion estiamtion scheme using the wavelet transformed multi-resolution image layers is proposed. Compared with the full search motion estimation method, the existing hierarchical methods remarkably reduce the amount of the computation but their efficiencies are depreciated by the local minima problem. In order to solve the local minima problem, the multi-resolution image layers are composed using the wavelet transform and the number of layers participated in the motion estimation for a block is determined by considering of its low band energy and higher band energy on the first wavelet transformed layer. The ratio between higher band energy and low band energy of each block is evaluated and in the case of the blocks which include relatively large higher band energy, the motion estimation is carried out in the high resolution layer. Otherwise, all layers are used. The final motion vectors are obtained in the first wavelet transformed layer. So less bits for motion vectors are transmitted, and the decomposition of received image using inverse wavelet transform decreases the blocking effect.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.05a
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• pp.232-235
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• 2000

In this paper, we introduce a new genetic reordering operator based on the concept of schema to solve the Traveling Salesman Problem(TSP). Because TSP is a well-known combinatorial optimization problem and belongs to a NP-complete problem, there is a huge solution space to be searched. For robustness to local minima, the operator separates selected strings into two parts to reduce the destructive probability of good building blocks. And it applies inversion to the schema part to prevent the premature convergence. At the same time, it searches new spaces of solutions. In addition, we have the non-schema part to be applied to inversion as well as for robustness to local minima. By doing so, we can preserve diversity of the distributions in population and make GA be adaptive to the dynamic environment.

• Journal of KIISE:Software and Applications
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• v.33 no.6
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• pp.574-579
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• 2006

The feature selection algorithms should broadly and efficiently explore the huge problem spaces to find a good solution. This paper attempts to gain insights on the fitness landscape of the spaces and to improve search capability of the algorithms. We investigate the solution spaces in terms of statistics on local maxima and minima. We also analyze behaviors of the existing algorithms and improve their solutions.

• Journal of KIISE:Software and Applications
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• v.33 no.12
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• pp.999-1007
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• 2006

The Backpropagation learning algorithm is known to have slow and false convergence aroused from plateau and local minima. Many substitutes for backpropagation announced so far appear to pay some trade-off for convergence speed and stability of convergence according to parameters. Here, a new algorithm is proposed, which avoids some of those problems associated with the conventional backpropagation problems, especially with local minima, and gives relatively stable and fast convergence with low storage requirement. This is the separate learning algorithm in which the upper connections, hidden-to-output, and the lower connections, input-to-hidden, separately trained. This algorithm requires less computational work than the conventional backpropagation and other improved algorithms. It is shown in various classification problems to be relatively reliable on the overall performance.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.14 no.6
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• pp.1375-1383
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• 1994

The water distribution system problem consists of finding a minimum cost system design subject to hydraulic and operational constraints. Since the municipal water distribution system problem is nonconvex with multiple local minima, classical optimization methods find a local optimum. An outer flow search - inner optimization procedure is proposed for choosing a better local minimum for the water distribution systems. The pipe network is judiciously subjected to the outer search scheme which chooses alternative flow configurations to find an optimal flow division among pipes. Because the problem is nonconvex, a global search scheme called Stochastic Probing method is employed to permit a local optimum seeking method to migrate among various local minima. A local minimizer is employed for the design of least cost diameters for pipes in the network. The algorithm can also be employed for optimal design of parallel expansion of existing networks. In this paper one municipal water distribution system is considered. The optimal solutions thus found have significantly smaller costs than the ones reported previously by other researchers.

• Proceedings of the Korea Concrete Institute Conference
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• 1994.10a
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• pp.267-272
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• 1994

This work presents a method of optimum design for reinforced concrete building frames with rectangular cross sections. The optimization techniques used is based on the principle of divided parameters. The design variable parameters are divided into two groups, external and internal, and the optimization is also divided into external and internal procedure. This principle overcomes difficulties arising from the presence of two materials in one element, the property peculiar to reinforced concrete. Several search algorithms are tested to verify their accuracy for the external optimization. Among them pattern search algorithms has been found consistent. This work proposes a new method, modified pattern search, and a number of sample problems prove its accuracy and usefulness. Exhaustive search for all local minima in the design spaces for two sample problems has been carried out to understand the nature of the problem. The number of local minima identified is quite more than expected and it has become understood that the researcher's task in this field is to find a better local minimum if not global. The designs produced by the method preposed have been found better than those from other method, and they are in full accord with ACI Building Code Requirments(ACI 318-89).