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4th IEEE International Conference on Applied System Invention (IEEE ICASI)

作者： Othman, Zulkifli Sulaiman, Shahril Irwan Musirin, Ismail Omar, Ahmad Maliki Shaari, Sulaiman Univ Teknol MARA Fac Elect Engn Shah Alam Selangor Malaysia Univ Teknol MARA Fac Appl Sci Shah Alam Selangor Malaysia

ISBN: (纸本)9781538643426

This paper presents a sizing optimization technique for Stand-Alone Photovoltaic (SAPV) system. Three optimization techniques were developed, namely Dolphin Echolocation (DE), fast evolutionary programming (FEP) and Classical evolutionary programming (CEP). These techniques had been incorporated into the sizing process to maximize the Performance Ratio (PR) of the system by determining the optimal PV modules, charge controllers, inverters, and batteries. The results showed that DE outperformed FEP and CEP in producing the highest PR.

关键词： Stand-Alone Photovoltaic Dolphin Echolocation Algorithm fast evolutionary programming Classical evolutionary programming Iterative Sizing Algorithm

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Dolphin Echolocation - Based Sizing Algorithm for Stand-Alone Photovoltaic System

Dolphin Echolocation - Based Sizing Algorithm for Stand-Alon...

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International Conference on Applied System Innovation

作者： Zulkifli Othman Shahril Irwan Sulaiman Ismail Musirin Ahmad Maliki Omar Sulaiman Shaari Faculty of Electrical Engineering Universiti Teknologi MARA Selangor Malaysia Faculty of Applied Sciences Universiti Teknologi MARA Selangor Malaysia

关键词： Stand-Alone Photovoltaic Dolphin Echolocation Algorithm fast evolutionary programming Classical evolutionary programming Iterative Sizing Algorithm

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Are Long Jumps of Cauchy Mutations Effective in fast evolutionary programming?

Are Long Jumps of Cauchy Mutations Effective in Fast Evoluti...

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2010 IEEE World Congress on Computational Intelligence

作者： Liu, Yong Univ Aizu Sch Comp Sci & Engn Fukushima 9658580 Japan

ISBN: (纸本)9781424481262

It had been discovered that not long jumps but short jumps with large variances among Cauchy mutations had contributed to the better performance of fast evolutionary programming (FEP) than that of classical evolutionary programming (CEP). One strong force to push the effective Cauchy mutations to have the shorter step sizes came from the different behaviors of the the same self-adaptation used in CEP and FEP on optimizing the same test functions from the same initial populations. This paper explored such correlation between the mutation step sizes and self-adaptation, and suggests that it is as necessary to set up an upper bound as to have a lower bound on the strategy parameters in self-adaptation.

关键词： Cauchy mutations classical evolutionary programming evolutionary computation fast evolutionary programming long jumps lower bound self-adaptation

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Dynamic Economic Dispatch Solution Using fast evolutionary programming with Swarm Direction

Dynamic Economic Dispatch Solution Using Fast Evolutionary P...

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4th IEEE Conference on Industrial Electronics and Applications

作者： Gaing, Zwe-Lee Ou, Ting-Chia Kao Yuan Univ Dept Elect Engn Kaohsiung 821 Taiwan Inst Nucl Energy Res Atom Energy Council Taoyuan Taiwan

ISBN: (纸本)9781424427994

This paper presented a fast evolutionary programming (FEP) with swarm direction for solving the dynamic economic dispatch (DED) problem in power systems. The proposed method employed the swarm directions to embed in fast evolutionary programming (SFEP) to enhance the performance of FEP algorithm. Many practical operating constraints of the generator, such as ramp rate limits and prohibited operating zone, are considered in solving the constrained DED problem. The feasibility of the proposed SFEP method is demonstrated for a 15-unit system, and it is compared with the other FEP-based methods in terms of solution quality and computation efficiency. The experimental results show that the proposed SFEP method was indeed capable of obtaining higher quality solutions efficiently in solving the non-convex DED problems.

关键词： dynamic economic dispatch fast evolutionary programming particle swarm optimization prohibited operating zone

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Effect of Multivariate Cauchy Mutation in evolutionary programming

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IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS 2014年第4期E97D卷 821-829页

作者： Lee, Chang-Yong Park, Yong-Jin Kongju Natl Univ Dept Ind & Syst Engn Kong Ju 314701 South Korea Kongju Natl Univ Dept Plant Resources Yesan 340802 South Korea

In this paper, we apply a mutation operation based on a multivariate Cauchy distribution to fast evolutionary programming and analyze its effect in terms of various function optimizations. The conventional fast evolutionary programming in-cooperates the univariate Cauchy mutation in order to overcome the slow convergence rate of the canonical Gaussian mutation. For a mutation of a variables, while the conventional method utilizes n independent random variables from a univariate Cauchy distribution, the proposed method adopts n mutually dependent random variables that satisfy a multivariate Cauchy distribution. The multivariate Cauchy distribution naturally has higher probabilities of generating random variables in inter-variable regions than the univariate Cauchy distribution due to the mutual dependence among variables. This implies that the multivariate Cauchy random variable enhances the search capability especially for a large number of correlated variables, and, as a result, is more appropriate for optimization schemes characterized by interdependence among variables. In this sense, the proposed mutation possesses the advantage of both the univariate Cauchy and Gaussian mutations. The proposed mutation is tested against various types of real-valued function optimizations. We empirically find that the proposed mutation outperformed the conventional Cauchy and Gaussian mutations in the optimization of functions having correlations among variables, whereas the conventional mutations showed better performance in functions of uncorrelated variables.

关键词： fast evolutionary programming mutation operation multivariate Cauchy distribution function optimization inseparable functions

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fast evolutionary programming techniques for short-term hydrothermal scheduling

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IEEE TRANSACTIONS ON POWER SYSTEMS 2003年第1期18卷 214-220页

作者： Sinha, N Chakrabarti, R Chattopadhyay, PK Jadavpur Univ Dept Elect Engn Kolkata 700032 W Bengal India

fast evolutionary programming techniques are applied for the solution of a short-term hydrothermal scheduling problem. evolutionary programming (EP)-based algorithms with Gaussian and other mutation techniques have been developed and tested on a multireservoir cascaded hydroelectric system having prohibited operating zones and a thermal unit with valve point loading. Numerical results show that all of the EP algorithms are capable of finding very nearly global solutions within a reasonable time but an EP algorithm with better of Gaussian and Cauchy mutations appears to be the best amongst all EPs in terms of convergence speed, solution time, and minimum cost.

关键词： Cauchy mutation classical evolutionary programming fast evolutionary programming Gaussian mutation hydrothermal scheduling

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fast evolutionary programming techniques for short-term hydrothermal scheduling

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ELECTRIC POWER SYSTEMS RESEARCH 2003年第2期66卷 97-103页

作者： Sinha, N Chakrabarti, R Chattopadhyay, PK Univ Jadavpur Dept Elect Engn Kolkata India

This paper presents fast evolutionary programming (FEP) techniques for solution of short-term hydro thermal scheduling problems. evolutionary programming (EP) based algorithms with Gaussian mutation and other fast mutation techniques have been developed for hydrothermal scheduling (HS) problems. Numerical results for a test case show that all the EP-algorithms are capable of finding very nearly global solutions within a reasonable time but EP-algorithm with better of Gaussian and Cauchy mutations was the best amongst all EPs in terms of convergence rate, solution time and success rate. (C) 2003 Published by Elsevier Science B.V.

关键词： classical evolutionary programming Gaussian mutation Cauchy mutation fast evolutionary programming hydrothermal scheduling

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Utilization of evolutionary algorithms for making the environmental game much more exciting

Utilization of evolutionary algorithms for making the enviro...

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International Conference on Control, Automation and Systems

作者： Baba, Norio Handa, Hisashi Information Science Osaka Kyoiku University Osaka Prefecture Japan Natural Science and Technology Okayama University Okayama City Japan

ISBN: (纸本)9788995003879

In this paper, we suggest that EAs could be utilized for making the Environmental Game become much more exciting. In particular, in order attain this objective, we try to utilize evolutionary Algorithms in the following steps: (1) First, we consider a new way for producing a return for each player. (2) Second, we utilize Multi-Objective evolutionary Algorithms (MOEAs) to generate various skilled players whose decision making concerning the investment to the chemical goods (and consideration toward environmental protection) can strongly affect the environmental state of the sea. (3) Further, we utilize evolutionary programming (EP) to derive appropriate rules which could be used to help players fully enjoy game playing. Several game playing (utilizing the new rule) by our students suggest the effectiveness of our approach.

关键词： environmental game gaming neural networks multi-objective evolutionary algorithms fast evolutionary programming educational gaming player's satisfaction

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Meta heuristic search algorithms for short-term hydrothermal scheduling

Meta heuristic search algorithms for short-term hydrothermal...

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5th International Conference on Machine Learning and Cybernetics

作者： Sinha, Nidul Lai, Loi-Lei NIT Dept Elect Engn Silchar India City Univ London Energy Syst Grp London England

ISBN: (纸本)1424400600

This paper presents the performances of meta heuristic search algorithms in solving short-term hydro thermal scheduling problems. Meta heuristic search algorithms like GA, CEP, FEP, IFEP and PSO have been developed for hydrothermal scheduling problems. The performances of the algorithms are demonstrated on a test case. It has been observed that all the algorithms are capable of finding very nearly global solutions within a reasonable time but PSO algorithm was found to be the most efficient amongst them in terms of convergence rate, solution time and success rate.

关键词： fast evolutionary programming particle swarm optimization hydro-thermal scheduling

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META HEURISTIC SEARCH ALGORITHMS FOR SHORT-TERM HYDROTHERMAL SCHEDULING

META HEURISTIC SEARCH ALGORITHMS FOR SHORT-TERM HYDROTHERMAL...

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2006 International Conference on Machine Learning and Cybernetics(IEEE第五届机器学习与控制论坛)

作者： NIDUL SINHA LOI-LEI LAI Electrical Engineering Department NIT Silchar India Energy Systems Group City University London UK

关键词： fast evolutionary programming particle swarm optimization hydro-thermal scheduling

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