An evolutionary programming based algorithm was proposed for color imagequantization. A novel hybrid mutation operator was disigned to improve the quantization quality, anda stochastic sampling scheme was also present...
详细信息
An evolutionary programming based algorithm was proposed for color imagequantization. A novel hybrid mutation operator was disigned to improve the quantization quality, anda stochastic sampling scheme was also presented for saving the run time. The experimental resultsdemonstrate the superior performance of the proposed algorithm in comparison with the GA basedalgorithm.
A cultural algorithm is analyzed and *** application of this algorithm for solving complex constrained optimization problems has also been discussed. In this approach,an improved evolutionary programming is used as a ...
详细信息
A cultural algorithm is analyzed and *** application of this algorithm for solving complex constrained optimization problems has also been discussed. In this approach,an improved evolutionary programming is used as a population space,in which a shift factor is proposed;according to the corresponding population space, the knowledge sources contained in the belief space of cultural algorithm are specifically designed and are used to guide the evolutionary search,The approach not only can maintain quite nicely the population diversity,but also can help to converge to the global optimal solution rapidly, which is validated by some experimental results.
Because there are slow evolutionary process and difficult smooth convergence in evolutionary programming algorithm, a mutation operator for distribution network reconfiguration is proposed. In order to guarantee that ...
详细信息
Because there are slow evolutionary process and difficult smooth convergence in evolutionary programming algorithm, a mutation operator for distribution network reconfiguration is proposed. In order to guarantee that new individuals from mutation is close to the optimal individual actively, times of topology restructure should be inversely proportional to evolutionary generations, and both selection operators for switch to open and to close should be set in the process of topology restructure. Simplified calculation methods of power loss of network, quadratic load moment and selection operators are given. The feasibility of method proposed above is verified in the system of the operation optimization and the assistant decision of the 10kV distribution network which is located in Shangqiu power supply bureau Henan Province.
In this paper, the Chaos-Parallel evolutionary programming algorithm is presented to solve the Flow-Shop scheduling problem. At first, the individuals of each sub-population in the parallel evolutionary programming ar...
详细信息
ISBN:
(纸本)7312012035
In this paper, the Chaos-Parallel evolutionary programming algorithm is presented to solve the Flow-Shop scheduling problem. At first, the individuals of each sub-population in the parallel evolutionary programming are found out in the search space by use of the ergodicity properties of chaos states, then each sub-population evolves independently and the best individuals are exchanged between them periodically. The simulation results demostrate that the new algorithm is efficient for optimizing large-scale manufacturing process and the better results can be achieved on both the calculating time and optimizing rate.
The nominal optimal tracker for the chaotic, nonlinear, interval system is first proposed in this paper. Initially we use an optimal linearization methodology to obtain the exact linear models of a class of discrete-t...
详细信息
The nominal optimal tracker for the chaotic, nonlinear, interval system is first proposed in this paper. Initially we use an optimal linearization methodology to obtain the exact linear models of a class of discrete-time, nonlinear, time-invariant systems at operating states of interest, so that the conventional tracker will work for the nonlinear systems. A prediction-based digital tracker using the state-matching digital redesign method from a predesigned, state-feedback, continuous-time tracker for a hybrid chaotic system is presented. Then, we discuss the case in which the system has unknown-but-bounded interval parameters. The proposed evolutionary programming (EP) technique yields the strongest species to survive, reproduce themselves, and create more outstanding offspring. The worst-case realization of the sampled-data, nonlinear, uncertain system represented by the interval form with respect to the implemented 'best' tracker is also found in this paper for demonstrating the effectiveness of the proposed tracker.
Increment of load demands will cause voltage decay in the system which may lead to voltage collapse and increase thermal effect to transmission line in the system. Thus, reactive power support is one of the alternativ...
详细信息
ISBN:
(纸本)9781467350723
Increment of load demands will cause voltage decay in the system which may lead to voltage collapse and increase thermal effect to transmission line in the system. Thus, reactive power support is one of the alternative available schemes that can be performed to the system other than employing installing compensating devices. One of the choices is optimal reactive power dispatched (RPD). Operating all generators for performing reactive power support to a power system may lead to non-economical results which is rather unnecessary. Therefore, effort should be taken in order to avoid all generators from full operational in the attempt to raise the voltage level and improve the voltage stability condition in the system. This paper presents a new approach for selecting the operating generator performed optimally using evolutionary programming (EP) technique in power system. The proposed technique determines the best combination of generator that should be dispatched in the system considering loss minimization or voltage stability improvement. Implementation on the proposed technique was realized on the IEEE 30-bus RTS. Complete implementations on numerous combinations have been conducted and results indicated that the proposed technique revealed the best combination of the operating generators for improving voltage stability in the system.
In this artical, four evolutionary programming algorithms (Standard EP, Meta-EP, Continuous Standard EP and Continuous Meta-EP algorithms) are applied to test to maximizing a solution against a highly multimodal test ...
详细信息
ISBN:
(纸本)9781424455140;9781424455157
In this artical, four evolutionary programming algorithms (Standard EP, Meta-EP, Continuous Standard EP and Continuous Meta-EP algorithms) are applied to test to maximizing a solution against a highly multimodal test objective function. We will use the same population size to compare the effectiveness of these four algorithms according to their success rate, average number of function evaluation and average best fitness. We experiments with different population size.
We introduce an evolutionary-programming-based method for designing robust and computationally efficient adaptive bandpass filters. These predictive filters are optimized for generating current references in active po...
详细信息
We introduce an evolutionary-programming-based method for designing robust and computationally efficient adaptive bandpass filters. These predictive filters are optimized for generating current references in active power filters (APFs). The accuracy (phase/amplitude) of the reference current is crucial in current-injection-type systems, because it directly affects the harmonics reduction ability of the APF. Our digital filtering approach has the following advantages: selective bandpass response, efficient attenuation of specific harmonic components, capability to handle typical frequency alteration, small number of multiplications, and structural simplicity. In addition, practically no prior knowledge of the electricity distribution network and its loading characteristics is needed for designing the current reference generator. In an illustrative example, the total harmonic distortion of an artificial current waveform was reduced from 36.7% to less than 3.7% within the line frequency range 49-51 Hz. The proposed scheme is a combination of the hard-computing (HC)-type multiplicative general parameter method and evolutionary programming that, on the other hand, is a constituent of soft computing (SC). Such open-minded fusion thinking is emerging among researchers and engineers, and it can potentially lead to efficient combinations of HC and SC methodologies-both on the algorithm level and on the system level.
There is growing world-wide and Australian interest in the greater potential role of distributed generation and demand-side resources within the electricity industry. These distributed resources can offer promising ec...
详细信息
There is growing world-wide and Australian interest in the greater potential role of distributed generation and demand-side resources within the electricity industry. These distributed resources can offer promising economic and environmental benefits for power system operation. There are considerable challenges, however, in developing modelling tools that can explore the operational value of such resources within restructured electricity industries. This paper describes a Dual evolutionary programming approach where software agents for power system resources co-evolve optimal operational behaviors over repeated power system simulations. The tool is applied to a simple case study exploring the potential operational synergies between significant PV penetrations and distributed energy storage options including controllable loads. The case study demonstrates this tool's capabilities in modelling the potentially complex operational behaviors of these distributed resources including stochastic PV outputs and loads with varying daily demand profiles, thermal energy storage, charging and discharging constraints and self-leakage.
evolutionary programming (EP) optimization technique is proposed for efficient profile reconstruction and imaging of buried dielectric targets of elliptical-cylindrical shape. In particular, the efficiency of EP-based...
详细信息
ISBN:
(纸本)9781509008643
evolutionary programming (EP) optimization technique is proposed for efficient profile reconstruction and imaging of buried dielectric targets of elliptical-cylindrical shape. In particular, the efficiency of EP-based optimization in finding the location, shape, relative permittivity, and tilt- angle of the two dimensional (2-D) buried dielectric elliptical-cylindrical targets is investigated and statistically compared with Particle Swarm Optimization (PSO) method. Numerical results indicate that evolutionary programming method, as its first reported implementation in subsurface imaging, has a significantly better overall performance than PSO and can be used as a simple, yet efficient and robust global optimization technique for the inverse profiling of buried objects.
暂无评论