• Journal of Industrial Technology
• /
• v.20 no.B
• /
• pp.27-34
• /
• 2000

The definition of flatness is given by ISO, ANSI, KS, etc. but those standards don't mention about the specific methods for the flatness. So various solution models that are based on the Minimum Zone Method have been proposed as an optimization problem for the minimax curve fitting. But it has been rare to compare some optimization algorithms to make a guideline for choosing better algorithms in this field. Hence this paper examined and compared Genetic Algorithm and Simplex Method to the evaluation of flatness. As a result, Genetic Algorithm gave the better or equal flatness than Simplex Method but it has the inefficiency caused from the large number of iteration. Therefore, in the future, another researches about alternative algorithms including Hybrid Genetic Algorithm should be achieved to improve the efficiency of Genetic Algorithm for the evaluation of flatness.

• Journal of Industrial Technology
• /
• v.22 no.B
• /
• pp.35-44
• /
• 2002

To find the optimal solution as rapidly and exactly as possible with Nelder-Mead simplex algorithm, the present values of the reflection, expansion, contraction and/or shrink parameters of this algorithm are needed to be changed at appropriate time during the search process. The reflection parameter is selected in this study in order to be changed because reflection, expansion and contraction process can be simultaneously effected by only this parameter. Two independent indices for determining whether the present value of the reflection parameter of this algorithm should be changed or not during the search process are suggested in this study. Those indices were made of the equations of Nelder-Mead simplex algorithm's convergence criterion and Dennis-Wood's convergence criterion, respectively. It is appeared that the optimal solution can be find with smaller numbers of objective function evaluation than the original Nelder-Mead's one with fixed parameter when the those indices are used during the search process. and the more remarkable reduction effect of the number of an objective function evaluation can be obtained when the latter index is used.

• Journal of Industrial Technology
• /
• v.22 no.A
• /
• pp.19-28
• /
• 2002

The Nelder-Mead simplex algorithm has been one of the most widely used methods for the nonlinear unconstrained optimization, since 1965. Recently, the new algorithm, (so-called the Fuzzy Simplex Algorithm), with fuzzy logic controllers for the expansion, reflection and contraction process of this algorithm has been proposed. In this paper, this new algorithm is developed. And, the formulation for the optimum design of the power screw's efficiency is made. And then, the developed fuzzy simplex algorithm as well as the original one is applied to this optimum design problem. The Fuzzy simplex algorithm results in a faster convergence in this problem, as reported in other study, too.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2006.05a
• /
• pp.164-170
• /
• 2006

This paper proposes a RSM-based hybrid evolutionary algorithm (RHEA) which combines the merits of the popular programs such as genetic algorithm (GA), tabu search method, response surface methodology (RSM). This algorithm, for improving the convergent speed that is thought to be the demerit of genetic algorithm, uses response surface methodology and simplex method. The mutation of GA offers random variety to finding the optimum solution. In this study, however, systematic variety can be secured through the use of tabu list. Efficiency of this method has been proven by applying traditional test functions and comparing the results to GA. And it was also proved that the newly suggested algorithm is very effective to find the global optimum solution to minimize the weight for avoiding the resonance of fresh water tank that is placed in the rear of ship. According to the study, GA's convergent speed in initial stages is improved by using RSM method. An optimized solution is calculated without the evaluation of additional actual objective function. In a summary, it is concluded that RHEA is a very powerful global optimization algorithm from the view point of convergent speed and global search ability.

• Transactions of the Korean Society for Noise and Vibration Engineering
• /
• v.16 no.6 s.111
• /
• pp.665-673
• /
• 2006

This paper proposes a RSM-based hybrid evolutionary Algorithm (RHEA) which combines the merits of the popular programs such as genetic algorithm (GA), tabu search method and response surface methodology (RSM). This algorithm, for improving the convergent speed that is thought to be the demerit of genetic algorithm, uses response surface methodology and simplex method. The mutation of GA offers random variety to finding the optimum solution. In this study, however, systematic variety can be secured through the use of tabu list. Efficiency of this method has been proven by applying traditional left functions and comparing the results to GA. It was also proved that the newly suggested algorithm is very effective to find the global optimum solution to minimize the weight for avoiding the resonance of fresh water tank that is placed in the after body area of ship. According to the study, GA's convergent speed in initial stages is improved by using RSM method. An optimized solution is calculated without the evaluation of additional actual objective function. In a summary, it is concluded that RHEA is a very powerful global optimization algorithm from the view point of convergent speed and global search ability.

• Journal of Navigation and Port Research
• /
• v.29 no.5 s.101
• /
• pp.409-413
• /
• 2005

The existing control techniques for the operation of a container crane satisfy the terminal condition of controlled variables, but the outcome of input computation is inadequate for the operation of the crane due to heavy movement of inputs. In this study, a new control technique employing a nonlinear model of the crane is proposed to compute the inputs approximated with the 4th-order Chevyshev function. The control objective of sum of absolute deviations is minimized, and the optimization is conducted with the simplex algorithm. The inputs and outputs computed from the proposed technique were compared with the results of the previous study to show that they give more stable crane operation than the existing control technique.