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Recent Advances in Evolutionary Computation

Journal of Computer Science & Technology 2006年第1期21卷 1-18页

作者：姚新徐永 Nature Inspired Computation and Applications Laboratory The University of Science and Technology of China Hefei 230027 P.R. China The Centre of Excellence for Research in Computational Intelligence and Applications (CERCIA)School of Computer Science The University of Birmingham Edgbaston Birmingham B15 2TT UK

Evolutionary computation has experienced a tremendous growth in the last decade in both theoretical analyses and industrial applications. Its scope has evolved beyond its original meaning of ＂biological evolution＂ toward a wide variety of nature inspired computational algorithms and techniques, including evolutionary, neural, ecological, social and economical computation, etc, in a unified framework. Many research topics in evolutionary computation nowadays are not necessarily ＂evolutionary＂. This paper provides an overview of some recent advances in evolutionary computation that have been made in CERCIA at the University of Birmingham, UK. It covers a wide range of topics in optimization, learning and design using evolutionary approaches and techniques, and theoretical results in the computational time complexity of evolutionary algorithms. Some issues related to future development of evolutionary computation are also discussed.

关键词： evolutionary computation neural network ensemble prisoner's dilemma real-world application computational time complexity

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Electrostatic energies and forces computed without explicit interparticle interactions: A linear time complexity formulation

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JOURNAL OF computational CHEMISTRY 2005年第8期26卷 755-787页

作者： Petrella, RJ Karplus, M Harvard Univ Dept Chem & Biol Chem Cambridge MA 02138 USA Univ Strasbourg Inst Le Bel F-67070 Strasbourg France

A rapid method for the calculation of the electrostatic energy of a system without a cutoff is described in which the computational time grows linearly with the number of particles or charges. The inverse of the distance is approximated as a polynomial, which is then transformed into a function whose terms involve individual particles, instead of particle pairs, by a partitioning of the double sum. In this way, the electrostatic energy that is determined by the interparticle interactions is obtained without explicit calculation of these interactions. For systems of positive charges positioned on a face-centered cubic lattice, the calculation of the energy by the new method is shown to be faster than the calculation of the exact energy, in many cases by an order of magnitude, and to be accurate to within 1-2%. The application of this method to increase the accuracy of conventional truncation-based calculations in condensed-phase systems is also demonstrated by combining the approximated long-range electrostatic interactions with the exact short-range interactions in a "hybrid" calculation. For a 20-angstrom sphere of water molecules, the forces are shown to be six times as accurate using this hybrid method as those calculated with conventional truncation of the electrostatic energy function at 12 A. This is accomplished with a slight increase in speed, and with a sevenfold increase in speed relative to the exact all-pair calculation. Structures minimized with the hybrid function are shown to be closer to structures minimized with an exact all-pair electrostatic energy function than are those minimized with a conventional 13-angstrom cutoff-based electrostatic energy function. Comparison of the energies and forces calculated with the exact method illustrate that the absolute errors obtained with standard truncation can be very large. The extension of the current method to other pairwise functions as well as to multibody functions, is described. (c) 2005 Wiley Periodic

关键词： sum reduction polynomial approximations electrostatic energy computational time complexity singlewise energy functions monoindexability

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Analysis of computational time of Simple Estimation of Distribution Algorithms

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IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION 2010年第1期14卷 1-22页

作者： Chen, Tianshi Tang, Ke Chen, Guoliang Yao, Xin Univ Sci & Technol China Nat Inspired Computat & Applicat Lab Sch Comp Sci & Technol Hefei 230027 Anhui Peoples R China Univ Birmingham Ctr Excellence Res Computat Intelligence & Applic Sch Comp Sci Birmingham B15 2TT W Midlands England

Estimation of distribution algorithms (EDAs) are widely used in stochastic optimization. Impressive experimental results have been reported in the literature. However, little work has been done on analyzing the computation time of EDAs in relation to the problem size. It is still unclear how well EDAs (with a finite population size larger than two) will scale up when the dimension of the optimization problem (problem size) goes up. This paper studies the computational time complexity of a simple EDA, i.e., the univariate marginal distribution algorithm (UMDA), in order to gain more insight into EDAs complexity. First, we discuss how to measure the computational time complexity of EDAs. A classification of problem hardness based on our discussions is then given. Second, we prove a theorem related to problem hardness and the probability conditions of EDAs. Third, we propose a novel approach to analyzing the computational time complexity of UMDA using discrete dynamic systems and Chernoff bounds. Following this approach, we are able to derive a number of results on the first hitting time of UMDA on a well-known unimodal pseudo-boolean function, i.e., the LeadingOnes problem, and another problem derived from LeadingOnes, named BVLeadingOnes. Although both problems are unimodal, our analysis shows that LeadingOnes is easy for the UMDA, while BVLeadingOnes is hard for the UMDA. Finally, in order to address the key issue of what problem characteristics make a problem hard for UMDA, we discuss in depth the idea of "margins" (or relaxation). We prove theoretically that the UMDA with margins can solve the BVLeadingOnes problem efficiently.

关键词： computational time complexity estimation of distribution algorithms first hitting time heuristic optimization univariate marginal distribution algorithms

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Empirical analysis of five nature-inspired algorithms on real parameter optimization problems

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ARTIFICIAL INTELLIGENCE REVIEW 2018年第3期50卷 383-439页

作者： Agarwal, Parul Mehta, Shikha Jaypee Inst Informat Technol Dept Comp Sci & Informat Technol Sect 62 Noida 201301 India

In the past few years nature-inspired algorithms are seen as potential tools to solve computationally hard problems. Tremendous success of these algorithms in providing near optimal solutions has inspired the researchers to develop new algorithms. However, very limited efforts have been made to identify the best algorithms for diverse classes of problems. This work attempts to assess the efficacy of five contemporary nature-inspired algorithms i.e. bat algorithm (BA), artificial bee colony algorithm (ABC), cuckoo search algorithm (CS), firefly algorithm (FA) and flower pollination algorithm (FPA). The work evaluates the performance of these algorithms on CEC2014 30 benchmark functions which include unimodal, multimodal, hybrid and composite problems over 10, 30, 50 and 100 dimensions. Control parameters of all algorithms are self-adapted so as to obtain best results over benchmark functions. The algorithms have been evaluated along three perspectives (a) statistical significance using Wilcoxon rank sum test (b) computational time complexity (c) convergence rate of algorithms. Experimental results and analysis revealed that ABC algorithm perform best for majority of the problems on high dimension, while on small dimension, CS is the best choice. FPA attain the next best position follow by BA and FA for all kinds of functions. Self adaptation of above algorithms also revealed the best values of input parameters for various algorithms. This study may aid experts and scientists of computational intelligence to solve intricate optimization problems.

关键词： Artificial bee colony algorithm computational time complexity Wilcoxon rank sum test Convergence rate

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A large population size can be unhelpful in evolutionary algorithms

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THEORETICAL COMPUTER SCIENCE 2012年 436卷 54-70页

作者： Chen, Tianshi Tang, Ke Chen, Guoliang Yao, Xin Univ Sci & Technol China Sch Comp Sci & Technol NICAL Hefei 230027 Anhui Peoples R China Chinese Acad Sci Inst Comp Technol Beijing 100190 Peoples R China Univ Birmingham Sch Comp Sci CERCIA Birmingham B15 2TT W Midlands England

The utilization of populations is one of the most important features of evolutionary algorithms (EAs). There have been many studies analyzing the impact of different population sizes on the performance of EAs. However, most of such studies are based on computational experiments, except for a few cases. The common wisdom so far appears to be that a large population would increase the population diversity and thus help an EA. Indeed, increasing the population size has been a commonly used strategy in tuning an EA when it did not perform as well as expected for a given problem. He and Yao (2002) [8] showed theoretically that for some problem instance classes, a population can help to reduce the runtime of an EA from exponential to polynomial time. This paper analyzes the role of population further in EAs and shows rigorously that large populations may not always be useful. Conditions, under which large populations can be harmful, are discussed in this paper. Although the theoretical analysis was carried out on one multimodal problem using a specific type of EAs, it has much wider implications. The analysis has revealed certain problem characteristics, which can be either the problem considered here or other problems, that lead to the disadvantages of large population sizes. The analytical approach developed in this paper can also be applied to analyzing EAs on other problems. (C) 2011 Elsevier B.V. All rights reserved.

关键词： Runtime analysis Evolutionary algorithms computational time complexity Evolutionary computation Combinatorial optimization

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Polymorphic Fuzzy Signatures

Polymorphic Fuzzy Signatures

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2010 IEEE World Congress on computational Intelligence

作者： Mendis, B. S. U. Gedeon, T. D. Australian Natl Univ Coll Engn & Comp Sci Sch Comp Sci Canberra ACT 0200 Australia

ISBN: (纸本)9781424469208

The fuzzy signature [1], [2] approach is aimed at finding a hierarchically decomposed solutions by adding new elements to Zadeh's approach [3]. It tackles the problem by splitting the problem into hierarchically organized local sub-models and by applying more complex and heterogenous descriptors, more fit for the identification of extremely complex models. However, the computational time complexity still affects the fuzzy signatures as we were attempt to create an atomic fuzzy signature for each data point we get. Importantly, the atomic fuzzy signatures we store has properties we can make use of to make search over this structure computationally efficient. In this paper we introduce a new approach that uses the metadata about a set of fuzzy signatures to extract a Polymorphic Fuzzy Signature. Productively, a polymorphic fuzzy signature represents its base set of fuzzy signatures in a higher meta level which also allows search/inference, and so can reduce the computational time complexity of the inference process.

关键词： Zadeh's approach atomic fuzzy signatures computational complexity computational time complexity data handling fuzzy reasoning fuzzy set theory heterogenous descriptors hierarchically decomposed solution inference process meta data metadata polymorphic fuzzy signatures

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Runtime Analysis of Estimation of Distribution Algorithms for a Simple Scheduling Problem 19th

Runtime Analysis of Estimation of Distribution Algorithms fo...

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19th International Conference on Advanced Intelligent Computing Technology and Applications (ICIC)

作者： Liu, Rui Qian, Bin Zhang, Sen Hu, Rong Yu, Nai-Kang Kunming Univ Sci & Technol Sch Informat Engn & Automat Kunming 650500 Yunnan Peoples R China

ISBN: (纸本)9789819947546;9789819947553

Estimation of Distribution Algorithm (EDA) is an intelligent optimization technique widely applied in production scheduling. In algorithm application, time complexity is an important criterion of concern. However, there is relatively little theoretical research on the time complexity of these algorithms. We propose a single machine scheduling with deteriorating effect (SMSDE) and give a proof of its property. Under the objective of minimizing the makespan, the convergence time (CT) of EDA to solve SMSDE is obtained. Then, we obtain the First Hitting time (FHT) of EDA solving SMSDE from CT. This study provides some theoretical support for the application of EDA.

关键词： Estimation of distribution algorithms first hitting time deteriorating effect computational time complexity

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Performance evaluation of all intra Kvazaar and x265 HEVC encoders on embedded system Nvidia Jetson platform

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JOURNAL OF REAL-time IMAGE PROCESSING 2024年第3期21卷 67-67页

作者： James, R. Abo-Zahhad, Mohammed Inoue, Koji Sayed, Mohammed S. Egypt Japan Univ Sci & Technol Dept Elect & Commun Engn New Borg El Arab City 21934 Alexandria Egypt Assiut Univ Dept Elect & Elect Engn Assiut 71515 Egypt Kyushu Univ Fac Informat Sci & Elect Engn Fukuoka Japan Zagazig Univ Dept Elect & Commun Engn Zagazig Egypt

The growing demand for high-quality video requires complex coding techniques that cost resource consumption and increase encoding time which represents a challenge for real-time processing on Embedded Systems. Kvazaar and x265 encoders are two efficient implementations of the High-Efficient Video Coding (HEVC) standard. In this paper, the performance of All Intra Kvazaar and x265 encoders on the Nvidia Jetson platform was evaluated using two coding configurations;highspeed preset and high-quality preset. In our work, we used two scenarios, first, the two encoders were run on the CPU, and based on the average encoding time Kvazaar proved to be 65.44% and 69.4% faster than x265 with 1.88% and 0.6% BD-rate improvement over x265 at high-speed and high-quality preset, respectively. In the second scenario, the two encoders were run on the GPU of the Nvidia Jetson, and the results show the average encoding time under each preset is reduced by half of the CPU-based scenario. In addition, Kvazaar is 54.5% and 56.70% faster with 1.93% and 0.45% BD-rate improvement over x265 at high-speed and high-quality preset, respectively. Regarding the scalability, the two encoders on the CPU are linearly scaled up to four threads and speed remains constant afterward. On the GPU, the two encoders are scaled linearly with the number of threads. The obtained results confirmed that, Kvazaar is more efficient and that it can be used on Embedded Systems for real-time video applications due to its high speed and performance over the x265 HEVC encoder

关键词： All intra computational time complexity Kvazaar HEVC encoder Jetson TX1 NVIDIA GPU x265 HEVC encoder

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