Publications (4)0 Total impact
Conference Paper: Differential Evolution with adaptive population size[Show abstract] [Hide abstract]
ABSTRACT: Differential Evolution (DE) is one of the evolutionary algorithms under active research. It has been successfully applied to many real-world problems. The performance of DE highly depends on the population size Np. An improper selection of Np may result in premature convergence or waste of computational resources. In this paper, we proposed a novel method to adaptively control the population size of DE. With this method users do not need to set the Np parameter for DE. The proposed algorithm DEAPS is compared with the conventional DE with different population sizes. DEAPS demonstrates encouraging results on its capability of adaption for seven problems of benchmark test functions.
Conference Paper: Economic load dispatch using intelligent optimization with fuzzy control[Show abstract] [Hide abstract]
ABSTRACT: In this paper, Differential Evolution (DE) that incorporates fuzzy control and k-nearest neighbors algorithm is proposed to tackle the economic load dispatch problem. To provide the self-terminating ability, a technique called Iteration Windows (IW) is introduced to govern the number of iteration in each searching stage during the optimization. The size of IW is controlled by a fuzzy controller, which uses the information provided by the k-nearest neighbors system to analyze the population during the searching process. The controller keeps controlling the IW till the end of the searching process. A wavelet based mutation process is embedded in the DE searching process to enhance the searching performance. The weight F of DE is also controlled by the fuzzy controller to further speed up the searching process. The proposed method is employed to solve the Economic Load Dispatch with Valve-Point Loading (ELD-VPL) Problem. It is shown empirically that the proposed method can terminate the searching process with a reasonable number of iteration and performs significantly better than the conventional methods in terms of convergence speed and solution quality.
Conference Paper: An adaptive differential evolution with unsymmetrical mutation[Show abstract] [Hide abstract]
ABSTRACT: Differential Evolution (DE) is one of the evolutionary algorithms under active research. It has been successfully applied to many real world problems. In this paper, an improved DE with a novel mutation scheme is proposed. The improved DE assigns a distinct scale factor for each individual mutation based on the fitness associated with each base vector involved in the mutation. With the adoption of different scale factors for mutation, DE is capable of searching more locally around superior points and explore more broadly around inferior points. Consequently, a good balance between exploration and exploitation can be achieved. Also, an adaptive base vector selection scheme is introduced to DE. This scheme is capable of estimating the complexity of objective functions based on the population variance. When the problem is simple, it will tend to select good vectors as base vector which will lead to quick convergence. When the objective function is complex, it will select base vector randomly so that the population maintains a high exploration capability and will not be trapped into local minima so easily. A suite of 12 benchmark functions are used to evaluate the performance of the proposed method. The simulation result shows that the proposed method is promising in terms of convergence speed, solution quality and stability.
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ABSTRACT: In this paper, an improved Differential Evolution (DE) that incorporates double wavelet-based operations is proposed to solve the Economic Load Dispatch (ELD) problem. The double wavelet mutations are applied in order to enhance DE in exploring the solution space more effectively for better solution quality and stability. The first stage of wavelet ope-ration is embedded in the DE mutation operation, in which the scaling factor is governed by a wavelet function. In the second stage, a wavelet-based mutation operation is embedded in the DE crossover operation. The trial population vec-tors are modified by the wavelet function. A suite of benchmark test functions is employed to evaluate the performance of the proposed DE in different problems. The result shows empirically that the proposed method out-performs signify-cantly the conventional methods in terms of convergence speed, solution quality and solution stability. Then the pro-posed method is applied to the Economic Load Dispatch with Valve-Point Loading (ELD-VPL) problem, which is a process to share the power demand among the online generators in a power system for minimum fuel cost. Two dif-ferent conditions of the ELD problem have been tested in this paper. It is observed that the proposed method gives satis-factory optimal costs when compared with the other techniques in the literature.
The Hong Kong Polytechnic University
Hong Kong, Hong Kong
- Department of Electronic and Information Engineering