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Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600)最新文献

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Efficient machine-code test-program induction 高效的机器码测试程序归纳
Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600) Pub Date : 2002-05-12 DOI: 10.1109/CEC.2002.1004462
F. Corno, G. Cumani, M. Sonza Reorda, Giovanni Squillero
{"title":"Efficient machine-code test-program induction","authors":"F. Corno, G. Cumani, M. Sonza Reorda, Giovanni Squillero","doi":"10.1109/CEC.2002.1004462","DOIUrl":"https://doi.org/10.1109/CEC.2002.1004462","url":null,"abstract":"Technology advances allow integrating an entire system on a single chip, including memories and peripherals. The testing of these devices is becoming a major issue for chip manufacturing industries. This paper presents a methodology, similar to genetic programming, for inducing test programs. However, it includes the ability to explicitly specify registers and resorts to directed acyclic graphs instead of trees. Moreover, it exploits a database containing the assembly-level semantics associated with each graph node. This approach is extremely efficient and versatile: candidate solutions are translated into source-code programs allowing millions of evaluations per second. The proposed approach is extremely versatile: the macro library allows the target processor and the environment to be changed easily. The approach was verified on three processors with different instruction sets, different formalisms and different conventions. A complete set of experiments on a test function is also reported for the SPARC processor.","PeriodicalId":184547,"journal":{"name":"Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600)","volume":"110 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128164213","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 22
Objective function decomposition within genetic algorithm 遗传算法中的目标函数分解
Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600) Pub Date : 2002-05-12 DOI: 10.1109/CEC.2002.1006260
K. G. Khoo, P. N. Suganthan
{"title":"Objective function decomposition within genetic algorithm","authors":"K. G. Khoo, P. N. Suganthan","doi":"10.1109/CEC.2002.1006260","DOIUrl":"https://doi.org/10.1109/CEC.2002.1006260","url":null,"abstract":"The genetic algorithm (GA) has been applied to numerous optimization problems since its introduction. Here, information on each element of the solution strings is extracted to improve the GA's performance. We decouple a fitness evaluation function, estimating the fitness contribution by each dimension. Using this information, each dimension within each solution fights for its position in the offspring. A comparison with the standard GA showed that the proposed GA is superior on commonly tested functions.","PeriodicalId":184547,"journal":{"name":"Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600)","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131386291","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Analysis of optimal trajectory on evolutionary algorithm and some control strategies 基于进化算法的最优轨迹分析及控制策略
Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600) Pub Date : 2002-05-12 DOI: 10.1109/CEC.2002.1006987
Yuanxiang Li, Lishan Kang
{"title":"Analysis of optimal trajectory on evolutionary algorithm and some control strategies","authors":"Yuanxiang Li, Lishan Kang","doi":"10.1109/CEC.2002.1006987","DOIUrl":"https://doi.org/10.1109/CEC.2002.1006987","url":null,"abstract":"In this article, we discuss a theory of the optimal trajectory for evolutionary algorithms from the optimal control theory of dynamical system. Control strategies are derived using theoretical results, such as the selection mechanism and the stopping condition for the design, analysis and application of evolutionary algorithms.","PeriodicalId":184547,"journal":{"name":"Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131948171","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Dynamic memory model for non-stationary optimization 非平稳优化的动态记忆模型
Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600) Pub Date : 2002-05-12 DOI: 10.1109/CEC.2002.1006224
C. Bendtsen, T. Krink
{"title":"Dynamic memory model for non-stationary optimization","authors":"C. Bendtsen, T. Krink","doi":"10.1109/CEC.2002.1006224","DOIUrl":"https://doi.org/10.1109/CEC.2002.1006224","url":null,"abstract":"Real-world problems are often nonstationary and can cause cyclic, repetitive patterns in the search landscape. For this class of problems, we introduce a new GA with dynamic explicit memory, which showed superior performance compared to a classic GA and a previously introduced memory-based GA for two dynamic benchmark problems.","PeriodicalId":184547,"journal":{"name":"Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130049446","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 57
Determining critical gust loads on aircraft structures using an evolutionary algorithm 用进化算法确定飞机结构的临界阵风荷载
Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600) Pub Date : 2002-05-12 DOI: 10.1109/CEC.2002.1007021
C. L. Karr, T. Zeiler, R. Mehrotra
{"title":"Determining critical gust loads on aircraft structures using an evolutionary algorithm","authors":"C. L. Karr, T. Zeiler, R. Mehrotra","doi":"10.1109/CEC.2002.1007021","DOIUrl":"https://doi.org/10.1109/CEC.2002.1007021","url":null,"abstract":"In this paper an evolutionary algorithm (EA) is shown to be a feasible approach to solving the problem of determining the characteristics of wind gusts that result in critical loading of aircraft structures. The EA outperforms a traditional method suitable for solving linear problems, and is then extended to nonlinear problems for which there is no effective solution methodology.","PeriodicalId":184547,"journal":{"name":"Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600)","volume":"90 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133585353","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Towards a genetic algorithms approach to designing 3D polygonal tree models 基于遗传算法的三维多边形树模型设计
Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600) Pub Date : 2002-05-12 DOI: 10.1109/CEC.2002.1004523
R. Mazza, C. Congdon
{"title":"Towards a genetic algorithms approach to designing 3D polygonal tree models","authors":"R. Mazza, C. Congdon","doi":"10.1109/CEC.2002.1004523","DOIUrl":"https://doi.org/10.1109/CEC.2002.1004523","url":null,"abstract":"The OpenGL graphics libraries (http://www.opengl.org) provide a powerful environment for programming three-dimensional virtual worlds, and are used in a wide variety of applications. However, the creation of individual 3D models to include within a virtual world is an arduous and time-consuming process. We have designed GenTree, an interactive system that uses genetic algorithms to evolve 3D tree models to be used in virtual environments. The system evolves a set of parameters used to render the trees, with a fitness function provided by user input. The initial system works with a modest set of parameters and uses relatively crude rectangles for rendering, but is able to evolve a variety of plant shapes, including deciduous trees, evergreens, and shrubbery.","PeriodicalId":184547,"journal":{"name":"Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132094894","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 5
Modeling genetic network by hybrid GP 基于混合GP的遗传网络建模
Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600) Pub Date : 2002-05-12 DOI: 10.1109/CEC.2002.1006249
S. Ando, E. Sakamoto, H. Iba
{"title":"Modeling genetic network by hybrid GP","authors":"S. Ando, E. Sakamoto, H. Iba","doi":"10.1109/CEC.2002.1006249","DOIUrl":"https://doi.org/10.1109/CEC.2002.1006249","url":null,"abstract":"We present an evolutionary modeling method for modeling genetic regulatory networks. The method features a hybrid algorithm of genetic programming with statistical analysis to derive systems of differential equations. Genetic programming and the least mean squares method were combined to identify a concise form of regulation between the variables from a given set of time series. Results of multiple runs were statistically analyzed to indicate the term with robust and significant influence. Our approach was evaluated in artificial data and real world data.","PeriodicalId":184547,"journal":{"name":"Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132293023","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 12
Design of multi-objective evolutionary algorithms: application to the flow-shop scheduling problem 多目标进化算法设计:在流水车间调度问题中的应用
Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600) Pub Date : 2002-05-12 DOI: 10.1109/CEC.2002.1004405
M. Basseur, Franck Seynhaeve, E. Talbi
{"title":"Design of multi-objective evolutionary algorithms: application to the flow-shop scheduling problem","authors":"M. Basseur, Franck Seynhaeve, E. Talbi","doi":"10.1109/CEC.2002.1004405","DOIUrl":"https://doi.org/10.1109/CEC.2002.1004405","url":null,"abstract":"Multi-objective optimization using evolutionary algorithms has been extensively studied in the literature. We propose formal methods to solve problems appearing frequently in the design of such algorithms. To evaluate the effectiveness of the introduced mechanisms, we apply them to the flow-shop scheduling problem. We propose a dynamic mutation Pareto genetic algorithm (GA) in which different genetic operators are used simultaneously in an adaptive manner, taking into account the history of the search. We present a diversification mechanism which combines sharing in the objective space as well as in the decision space, in which the size of the niche is automatically calculated. We also propose a hybrid approach which combines the Pareto GA with local search. Finally, we propose two performance indicators to evaluate the effectiveness of the introduced mechanisms.","PeriodicalId":184547,"journal":{"name":"Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127072283","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 72
Autonomous registration of disparate spatial data via an evolutionary algorithm toolbox 通过进化算法工具箱对不同空间数据进行自主注册
Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600) Pub Date : 2002-05-12 DOI: 10.1109/CEC.2002.1006205
K. Tan, K. Sengupta, Tong-heng Lee, Ramasubramanian Sathikannan
{"title":"Autonomous registration of disparate spatial data via an evolutionary algorithm toolbox","authors":"K. Tan, K. Sengupta, Tong-heng Lee, Ramasubramanian Sathikannan","doi":"10.1109/CEC.2002.1006205","DOIUrl":"https://doi.org/10.1109/CEC.2002.1006205","url":null,"abstract":"In this paper, we present the registration of disparate spatial data. To be specific, we consider the registration of digital terrain elevation data (DTED) to National High Altitude Photography (NHAP). Initially, the DTED is shaded to form a synthetic image, and our registration process maps point in the shaded image to points in the NHAP. For the purpose of comparison, we propose two distinct techniques for matching. The first method is a semi-autonomous. It requires two pairs of user defined matched points to estimate an initial transform as starting point in the search for the best fitting transform using Nelder-Mead Simplex Method. The second method, being more novel in nature, attempts to eliminate the need for any user intervention and registers the two data autonomously by employing the Multi Objective Evolutionary Algorithm (MOEA) toolbox. Both methods worked well in estimating the best fitting affine transform to register the image and elevation data, and the MOEA based autonomous technique outperforms the much simpler single objective based semi autonomous technique.","PeriodicalId":184547,"journal":{"name":"Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600)","volume":"197 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133852475","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
All binary representations are equal: but some are more equal than others 所有二进制表示都是相等的:但有些比其他的更相等
Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600) Pub Date : 2002-05-12 DOI: 10.1109/CEC.2002.1006989
K. Willadsen, Janet Wiles
{"title":"All binary representations are equal: but some are more equal than others","authors":"K. Willadsen, Janet Wiles","doi":"10.1109/CEC.2002.1006989","DOIUrl":"https://doi.org/10.1109/CEC.2002.1006989","url":null,"abstract":"The original demonstration by G. Hinton and S. Nowlan (1987) of the Baldwin effect (J. Baldwin, 1896) is well-known and serves as an interesting basis for genetic algorithm (GA) research. A variant of the original representation used a binary code, in which learning was expressed as a substitute for internalised knowledge; in this paper, the representation is altered such that learning becomes an expression of uncertainty. This change results in an interesting and non-trivial set of interactions between the GA operators and the representation, as well as enhancing the performance and robustness of the GA.","PeriodicalId":184547,"journal":{"name":"Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600)","volume":"145 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115192981","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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