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Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753)最新文献

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Noisy optimization problems - a particular challenge for differential evolution? 噪声优化问题-微分进化的一个特殊挑战?
Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753) Pub Date : 2004-06-19 DOI: 10.1109/CEC.2004.1330876
T. Krink, B. Filipič, G. Fogel
{"title":"Noisy optimization problems - a particular challenge for differential evolution?","authors":"T. Krink, B. Filipič, G. Fogel","doi":"10.1109/CEC.2004.1330876","DOIUrl":"https://doi.org/10.1109/CEC.2004.1330876","url":null,"abstract":"The popularity of search heuristics has lead to numerous new approaches in the last two decades. Since algorithm performance is problem dependent and parameter sensitive, it is difficult to consider any single approach as of greatest utility overall problems. In contrast, differential evolution (DE) is a numerical optimization approach that requires hardly any parameter tuning and is very efficient and reliable on both benchmark and real-world problems. However, the results presented in this paper demonstrate that standard methods of evolutionary optimization are able to outperform DE on noisy problems when the fitness of candidate solutions approaches the fitness variance caused by the noise.","PeriodicalId":152088,"journal":{"name":"Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115054308","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: 145
Fast immunized evolutionary programming 快速免疫进化程序
Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753) Pub Date : 2004-06-19 DOI: 10.1109/CEC.2004.1330922
Wei Gao
{"title":"Fast immunized evolutionary programming","authors":"Wei Gao","doi":"10.1109/CEC.2004.1330922","DOIUrl":"https://doi.org/10.1109/CEC.2004.1330922","url":null,"abstract":"Evolutionary programming is a good global optimization method. By introduction, the improved adaptive mutation operation and improved selection operation based on thickness adjustment of artificial immune system into traditional evolutionary programming, a fast immunized evolutionary programming is proposed in this paper. At last, this algorithm is verified by simulation experiment of typical optimization function. The results of experiment show that, the proposed fast immunized evolutionary programming can improve not only the convergent speed of original algorithm but also the computation effect of original algorithm, and is a very good optimization method.","PeriodicalId":152088,"journal":{"name":"Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116808515","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: 25
Understanding the role of insertion and correction in the evolution of Golomb rulers 了解插入和校正在戈仑尺演变中的作用
Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753) Pub Date : 2004-06-19 DOI: 10.1109/CEC.2004.1330839
J. Tavares, F. B. Pereira, E. Costa
{"title":"Understanding the role of insertion and correction in the evolution of Golomb rulers","authors":"J. Tavares, F. B. Pereira, E. Costa","doi":"10.1109/CEC.2004.1330839","DOIUrl":"https://doi.org/10.1109/CEC.2004.1330839","url":null,"abstract":"An evolutionary algorithm designed to successfully search for Optimal Golomb rulers is presented. The proposed approach uses a binary representation to codify the marks contained in a ruler. Standard genetic operators are used. During evaluation, insertion and correction procedures are applied in order to improve the algorithm performance. Experimental results show that this approach is effective and capable of identifying good solutions. Furthermore, a comprehensive study is performed to understand the role of insertion and correction. Results reveal that the first method is essential to the success of the search process, whereas the importance of the second one remains unclear.","PeriodicalId":152088,"journal":{"name":"Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124604138","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: 11
Handling boundary constraints for numerical optimization by particle swarm flying in periodic search space 周期搜索空间中粒子群飞行的数值优化边界约束处理
Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753) Pub Date : 2004-06-19 DOI: 10.1109/CEC.2004.1331185
Wenjun Zhang, Xiao-Feng Xie, De-Chun Bi
{"title":"Handling boundary constraints for numerical optimization by particle swarm flying in periodic search space","authors":"Wenjun Zhang, Xiao-Feng Xie, De-Chun Bi","doi":"10.1109/CEC.2004.1331185","DOIUrl":"https://doi.org/10.1109/CEC.2004.1331185","url":null,"abstract":"The periodic mode is analyzed together with two conventional boundary handling modes for particle swarm. By providing an infinite space that comprises periodic copies of original search space, it avoids possible disorganizing of particle swarm that is induced by the undesired mutations at the boundary. The results on benchmark functions show that particle swarm with periodic mode is capable of improving the search performance significantly, by compared with that of conventional modes and other algorithms.","PeriodicalId":152088,"journal":{"name":"Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124855404","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: 92
Parallel differential evolution 并行差分演化
Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753) Pub Date : 2004-06-19 DOI: 10.1109/CEC.2004.1331145
D. Tasoulis, N. Pavlidis, V. Plagianakos, M. Vrahatis
{"title":"Parallel differential evolution","authors":"D. Tasoulis, N. Pavlidis, V. Plagianakos, M. Vrahatis","doi":"10.1109/CEC.2004.1331145","DOIUrl":"https://doi.org/10.1109/CEC.2004.1331145","url":null,"abstract":"Parallel processing has emerged as a key enabling technology in modern computing. Recent software advances have allowed collections of heterogeneous computers to be used as a concurrent computational resource. In this work we explore how differential evolution can be parallelized, using a ring-network topology, so as to improve both the speed and the performance of the method. Experimental results indicate that the extent of information exchange among subpopulations assigned to different processor nodes, bears a significant impact on the performance of the algorithm. Furthermore, not all the mutation strategies of the differential evolution algorithm are equally sensitive to the value of this parameter.","PeriodicalId":152088,"journal":{"name":"Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129852810","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: 246
Interactive multi-participant tour allocation 互动式多参与者旅游分配
Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753) Pub Date : 2004-06-19 DOI: 10.1109/CEC.2004.1331100
Pablo Funes, E. Bonabeau, J. Herve, Yves Morieux
{"title":"Interactive multi-participant tour allocation","authors":"Pablo Funes, E. Bonabeau, J. Herve, Yves Morieux","doi":"10.1109/CEC.2004.1331100","DOIUrl":"https://doi.org/10.1109/CEC.2004.1331100","url":null,"abstract":"We use the example of the allocation of tours to mailmen to illustrate the general idea that interactive evolutionary computation (IEC) can be applied to a range of task allocation problems where the task performers are humans. In this application of IEC, each participant is presented only with the portion of solution corresponding to his/her task (tour). In addition to the subjective evaluation of solutions by the participants, the solutions presented to the participants are pre-optimized according to objective criteria.","PeriodicalId":152088,"journal":{"name":"Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129576109","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: 13
Evolution strategies for multivariate-to-anything partially specified random vector generation 多变量到任意部分指定随机向量生成的进化策略
Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753) Pub Date : 2004-06-19 DOI: 10.1109/CEC.2004.1331175
S. Stanhope
{"title":"Evolution strategies for multivariate-to-anything partially specified random vector generation","authors":"S. Stanhope","doi":"10.1109/CEC.2004.1331175","DOIUrl":"https://doi.org/10.1109/CEC.2004.1331175","url":null,"abstract":"Multivariate-to-anything methods for partially specified random vector generation work by transforming samples from a driving distribution into samples characterized by given marginals and correlations. The correlations of the transformed random vector are controlled by the driving distribution; sampling a partially specified random vector requires finding an appropriate driving distribution. This paper motivates the use of evolution strategies for solving such problems and compares evolution strategies to conjugate gradient methods in the context of solving a Dirichlet-to-anything transformation. It is shown that the evolution strategy is at least as effective as the conjugate gradient method for solution of the parameterization problem.","PeriodicalId":152088,"journal":{"name":"Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753)","volume":"2265 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127472089","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
A hybrid algorithm for k-medoid clustering of large data sets 大数据集k-媒质聚类的混合算法
Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753) Pub Date : 2004-06-19 DOI: 10.1109/CEC.2004.1330840
Weiguo Sheng, Xiaohui Liu
{"title":"A hybrid algorithm for k-medoid clustering of large data sets","authors":"Weiguo Sheng, Xiaohui Liu","doi":"10.1109/CEC.2004.1330840","DOIUrl":"https://doi.org/10.1109/CEC.2004.1330840","url":null,"abstract":"In this paper, we propose a novel local search heuristic and then hybridize it with a genetic algorithm for k-medoid clustering of large data sets, which is an NP-hard optimization problem. The local search heuristic selects k-medoids from the data set and tries to efficiently minimize the total dissimilarity within each cluster. In order to deal with the local optimality, the local search heuristic is hybridized with a genetic algorithm and then the Hybrid K-medoid Algorithm (HKA) is proposed. Our experiments show that, compared with previous genetic algorithm based k-medoid clustering approaches - GCA and RAR/sub w/GA, HKA can provide better clustering solutions and do so more efficiently. Experiments use two gene expression data sets, which may involve large noise components.","PeriodicalId":152088,"journal":{"name":"Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128920853","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: 45
Particle swarm optimization algorithm for single machine total weighted tardiness problem 单机总加权延迟问题的粒子群优化算法
Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753) Pub Date : 2004-06-19 DOI: 10.1109/CEC.2004.1331062
M. Tasgetiren, M. Sevkli, Yun-Chia Liang, Gunes Gencyilmaz
{"title":"Particle swarm optimization algorithm for single machine total weighted tardiness problem","authors":"M. Tasgetiren, M. Sevkli, Yun-Chia Liang, Gunes Gencyilmaz","doi":"10.1109/CEC.2004.1331062","DOIUrl":"https://doi.org/10.1109/CEC.2004.1331062","url":null,"abstract":"In This work we present a particle swarm optimization algorithm to solve the single machine total weighted tardiness problem. A heuristic rule, the smallest position value (SPV) rule, is developed to enable the continuous particle swarm optimization algorithm to be applied to all classes of sequencing problems, which are NP-hard in the literature. A simple but very efficient local search method is embedded in the particle swarm optimization algorithm. The computational results show that the particle swarm algorithm is able to find the optimal and best-known solutions on all instances of widely used benchmarks from the OR library.","PeriodicalId":152088,"journal":{"name":"Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125676007","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: 220
Optimisation of the high efficiency deep grinding process with fuzzy fitness function and constraints 基于模糊适应度函数和约束的高效深磨削工艺优化
Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753) Pub Date : 2004-06-19 DOI: 10.1109/CEC.2004.1330909
P. Jones, A. Tiwari, R. Roy, J. Corbett
{"title":"Optimisation of the high efficiency deep grinding process with fuzzy fitness function and constraints","authors":"P. Jones, A. Tiwari, R. Roy, J. Corbett","doi":"10.1109/CEC.2004.1330909","DOIUrl":"https://doi.org/10.1109/CEC.2004.1330909","url":null,"abstract":"This paper describes the application of two multi-objective optimisation techniques to the high efficiency deep grinding process. The process is modelled using a fuzzy expert system. This allows understanding gained through theoretical analysis to be combined with empirical data in a solitary model. The objective is to simultaneously minimise the surface temperature and specific grinding energy. A problem constraint is represented within the fuzzy model. It forms an objective representing the degree of feasibility of the solution.","PeriodicalId":152088,"journal":{"name":"Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123735732","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
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