• Journal of Computing Science and Engineering
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• v.8 no.4
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• pp.199-206
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• 2014

The ant colony optimization (ACO) algorithm is a new heuristic algorithm that offers good robustness and searching ability. With in-depth exploration, the ACO algorithm exhibits slow convergence speed, and yields local optimization solutions. Based on analysis of the ACO algorithm and the genetic algorithm, we propose a novel hybrid genetic ant colony optimization (NHGAO) algorithm that integrates multi-population strategy, collaborative strategy, genetic strategy, and ant colony strategy, to avoid the premature phenomenon, dynamically balance the global search ability and local search ability, and accelerate the convergence speed. We select the traveling salesman problem to demonstrate the validity and feasibility of the NHGAO algorithm for solving complex optimization problems. The simulation experiment results show that the proposed NHGAO algorithm can obtain the global optimal solution, achieve self-adaptive control parameters, and avoid the phenomena of stagnation and prematurity.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.10 no.4
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• pp.398-410
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• 1998

Two-phase flow phenomena are observed in many industrial facilities and make much importance of optimum design for nuclear power plant and the liquid transportation system. The particular flow pattern depends on the conditions of pressure, flow velocity, and channel geometry. However, the research on drag reduction in two-phase flow is not intensively investigated. Therefore, experimental investigations have been carried out to analyze the drag reduction and void fraction by polymer addition in the two-phase flow system. We find that the polymer solution changes the characteristic of two-phase flow. The peak position of local void friction moves from tile wall of the pipe to the center of the pipe when polymer concentration increase. And then we predict that it is closely related with the frau reduction.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.11a
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• pp.157-160
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• 2000

This paper deals with the fuzzy modeling for the complex and uncertain system in which conventional and mathematical models may fail to give satisfactory results. mGA(messy Genetic Algorithm) has more effective and adaptive structure than sGA with respect to using changeable-length string and VEGA(Virus Evolution Genetic) Algorithm) can search the global and local optimal solution simultaneously with reverse transcription operator and transduction operator. Therefore in this paper, the optimal fuzzy model is obtained using Virus-messy Genetic Algorithm(Virus-mGA). In this method local information is exchanged in population so that population may sustain genetic divergence. To prove the surperioty of the proposed approach, we provide the numerical example.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.652-658
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• 1998

We introduce the concept of a bi-population scheme for real-coded GAs consisting of an explorer sub-Ga and an exploiter sub-GA. The explorer sub-GA mainly performs global exploration of the search space, and incorporates a restart mechanism to help avoid being trapped at local optima. The exploiter sub-GA performs exploitation of fit local areas of the search space around the neighborhood of the best-so-far solution. Thus the search function of the algorithm is divided. the proposed technique exhibits performance significantly superior to standard GAs on two complex highly multimodal problems.

• International Journal of Precision Engineering and Manufacturing
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• v.8 no.1
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• pp.3-10
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• 2007

A new approach based on implicit surface interpolation combined with domain decomposition is proposed for filling complex-shaped holes in a large polygon model, A surface was constructed by creating a smooth implicit surface from an incomplete polygon model through which the actual surface would pass. The implicit surface was defined by a radial basis function, which is a continuous scalar-value function over the domain $R^{3}$. The generated surface consisted of the set of all points at which this scalar function is zero. It was created by placing zero-valued constraints at the vertices of the polygon model. The well-known domain decomposition method was used to treat the large polygon model. The global domain of interest was divided into smaller domains in which the problem could be solved locally. The LU decomposition method was used to solve the set of small local problems; the local solutions were then combined using weighting coefficients to obtain a global solution. The validity of this new approach was demonstrated by using it to fill various holes in large and complex polygon models with arbitrary topologies.

• Journal of the korean Society of Automotive Engineers
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• v.11 no.1
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• pp.20-30
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• 1989

The unsteady conjugate forced convection-conduction heat transfer from a plate fin is numerically studied. The external forced flow is steady but the temperature of the fin base is an exponential change with time. Therefore, the unsteady energy equations of the fluid and the fin are solved simultaneously under the conditions of equality in heat flux and temperature at the fluid-fin interface at every instant of time. Numerical results are given for various quantities of interest including the local heat transfer coefficient, the local heat flux, the total heat transfer rate and the temperature distribution of fin under the effects of the convection-conduction parameter and the ratio of thermal diffusivities. The results of the present numerical solution have been compared with those of the conventional fin theory.

• Journal of the Korean Operations Research and Management Science Society
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• v.24 no.2
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• pp.121-134
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• 1999

In this paper, I propose a hybrid genetic algorithm(HGAM) incorporating a greedy interchange local optimization procedure for the multiobjective vehicle scheduling problems with service due times where three conflicting objectives of the minimization of total vehicle travel time, total weighted tardiness, and fleet size are explicitly treated. The vehicle is allowed to visit a node exceeding its due time with a penalty, but within the latest allowable time. The HGAM applies a mixed farming and migration strategy in the evolution process. The strategy splits the population into sub-populations, all of them evolving independently, and applys a local optimization procedure periodically to some best entities in sub-populations which are then substituted by the newly improved solutions. A solution of the HCAM is represented by a diploid structure. The HGAM uses a molified PMX operator for crossover and new types of mutation operator. The performance of the HGAM is extensively evaluated using the Solomons test problems. The results show that the HGAM attains better solutions than the BC-saving algorithm, but with a much longer computation time.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.2
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• pp.201-210
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• 2000

The large deflection of plate is analyzed by co-rotational formulations using small local displacements and rotating unit vectors on the nodal points. The rotational degrees of the freedom are represent ed by the unit vectors1 In the nodal points, and the equilibrium equations are formulated by using small deflection theories of the plates by assuming that the directions of the unit vectors of the nodal points are known apriori. The translational degrees of freedom are independently solved from the rotational degrees of freedom in the equilibrium equations, and the correct directions of the unit vectors are computed by the iterative scheme by imposing the moment equilibrium constraint. The equilibrium equations and the associated solution procedure are explained, and the verification problems are solved.

• Journal of Information Processing Systems
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• v.14 no.2
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• pp.448-454
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• 2018

Artificial bee colony (ABC) algorithm has attracted significant interests recently for solving the multivariate optimization problem. However, it still faces insufficiency of slow convergence speed and poor local search ability. Therefore, in this paper, a modified ABC algorithm with bees' number reallocation and new search equation is proposed to tackle this drawback. In particular, to enhance solution accuracy, more bees in the population are assigned to execute local searches around food sources. Moreover, elite vectors are adopted to guide the bees, with which the algorithm could converge to the potential global optimal position rapidly. A series of classical benchmark functions for frequency-modulated sound waves are adopted to validate the performance of the modified ABC algorithm. Experimental results are provided to show the significant performance improvement of our proposed algorithm over the traditional version.

• The Transactions of the Korea Information Processing Society
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• v.7 no.7
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• pp.2188-2195
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• 2000

This paper deals with the problem of determining small-bands enclosing a given set of points on the sphere. The small-band is a spherical region, whose boundary is composed of two circles, and which does not contain any great circle. It is a kind of domains that is derived from formalizing the local accessibility problems for 3-axis NC machining into sperical containment problems so as to avoid the grouping. It also can be generated in 4- and 5-axis machine. When a set of points U and the size of a great-band are given, the methods for computing a feasible band and all feasible bands enclosing U in O(n) and O(n log n) time have been suggested, respectively. The methods can be applied into the cases of small bands since the solution region may contain holes. In this paper, we concentrate on the method for determining the smallest small-band enclosing U and suggest an O(n long n) time algorithm, where n is the number of points on the sphere.