Proceedings of the 2000 Congress on Evolutionary Computation. CEC00 (Cat. No.00TH8512)最新文献

Test-case generator TCG-2 for nonlinear parameter optimisation 用于非线性参数优化的测试用例生成器TCG-2

Proceedings of the 2000 Congress on Evolutionary Computation. CEC00 (Cat. No.00TH8512) Pub Date : 2000-09-18 DOI: 10.1109/CEC.2000.870370

Martin Schmidt, Z. Michalewicz

引用次数: 23

Accelerating multi-objective control system design using a neuro-genetic approach 用神经遗传方法加速多目标控制系统设计

Proceedings of the 2000 Congress on Evolutionary Computation. CEC00 (Cat. No.00TH8512) Pub Date : 2000-09-01 DOI: 10.1109/CEC.2000.870322

N. M. Duarte, A. Ruano, C. Fonseca, P. Fleming

引用次数: 14

Automated timetable generation for rounds of a table-tennis league 自动生成乒乓球联赛回合的时间表

Proceedings of the 2000 Congress on Evolutionary Computation. CEC00 (Cat. No.00TH8512) Pub Date : 2000-07-16 DOI: 10.1109/CEC.2000.870307

Jörn Schönberger, D. Mattfeld, H. Kopfer

引用次数: 20

Evolutionary construction of behavior arbitration mechanisms based on dynamically-rearranging neural networks 基于动态重排神经网络的行为仲裁机制演化构建

Proceedings of the 2000 Congress on Evolutionary Computation. CEC00 (Cat. No.00TH8512) Pub Date : 2000-07-16 DOI: 10.1109/CEC.2000.870290

H. Nakamura, A. Ishiguro, Y. Uchilkawa

引用次数: 13

COSEARCH: a co-evolutionary metaheuristic COSEARCH:一个共同进化的元启发式

Proceedings of the 2000 Congress on Evolutionary Computation. CEC00 (Cat. No.00TH8512) Pub Date : 2000-07-16 DOI: 10.1109/CEC.2000.870839

V. Bachelet, E. Talbi

引用次数: 16

An efficient evolutionary algorithm for the degree-constrained minimum spanning tree problem 度约束最小生成树问题的一种有效进化算法

Proceedings of the 2000 Congress on Evolutionary Computation. CEC00 (Cat. No.00TH8512) Pub Date : 2000-07-16 DOI: 10.1109/CEC.2000.870282

G. Raidl

{"title":"An efficient evolutionary algorithm for the degree-constrained minimum spanning tree problem","authors":"G. Raidl","doi":"10.1109/CEC.2000.870282","DOIUrl":"https://doi.org/10.1109/CEC.2000.870282","url":null,"abstract":"The representation of candidate solutions and the variation operators are fundamental design choices in an evolutionary algorithm (EA). This paper proposes a novel representation technique and suitable variation operators for the degree-constrained minimum spanning tree problem. For a weighted, undirected graph G(V, E), this problem seeks to identify the shortest spanning tree whose node degrees do not exceed an upper bound d/spl ges/2. Within the EA, a candidate spanning tree is simply represented by its set of edges. Special initialization, crossover, and mutation operators are used to generate new, always feasible candidate solutions. In contrast to previous spanning tree representations, the proposed approach provides substantially higher locality and is nevertheless computationally efficient; an offspring is always created in O(|V|) time. In addition, it is shown how problem-dependent heuristics can be effectively incorporated into the initialization, crossover, and mutation operators without increasing the time-complexity. Empirical results are presented for hard problem instances with up to 500 vertices. Usually, the new approach identifies solutions superior to those of several other optimization methods within few seconds. The basic ideas of this EA are also applicable to other network optimization tasks.","PeriodicalId":218136,"journal":{"name":"Proceedings of the 2000 Congress on Evolutionary Computation. CEC00 (Cat. No.00TH8512)","volume":"231 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116394929","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: 118

Searching the forest: using decision trees as building blocks for evolutionary search in classification databases 搜索森林:使用决策树作为分类数据库进化搜索的构建块

Proceedings of the 2000 Congress on Evolutionary Computation. CEC00 (Cat. No.00TH8512) Pub Date : 2000-07-16 DOI: 10.1109/CEC.2000.870357

S. Rouwhorst, A. Engelbrecht

引用次数: 44

GP-based modeling method for time series prediction with parameter optimization and node alternation 基于gp的参数优化节点交替时间序列预测建模方法

Proceedings of the 2000 Congress on Evolutionary Computation. CEC00 (Cat. No.00TH8512) Pub Date : 2000-07-16 DOI: 10.1109/CEC.2000.870828

I. Yoshihara, T. Aoyama, M. Yasunaga

引用次数: 10

A novel hybrid evolutionary programming method for function optimization 一种新的函数优化混合进化规划方法

Proceedings of the 2000 Congress on Evolutionary Computation. CEC00 (Cat. No.00TH8512) Pub Date : 2000-07-16 DOI: 10.1109/CEC.2000.870366

A. Swain, A. Morris

{"title":"A novel hybrid evolutionary programming method for function optimization","authors":"A. Swain, A. Morris","doi":"10.1109/CEC.2000.870366","DOIUrl":"https://doi.org/10.1109/CEC.2000.870366","url":null,"abstract":"The basic evolutionary programming (BEP) method utilizes individual parent fitness to generate offspring. This is objectionable in many optimization problems, where the fitness value grows rapidly with problem dimensions, and two optimization problems differ by simply a scale factor. This paper is concerned with the development of an evolutionary programming method, which is functionally, and structurally equivalent to BEP, but still can be used effectively to optimize functions having strong fitness dependency between parents and their offspring. In this paper, a fitness-blind mutation (FBM) algorithm has been proposed, and then this is used in conjunction with the BEP mutation operator. The FBM operation has been implemented by taking the standard deviation of the Gaussian variable to vary in proportion to the genotypic distance between the individual parent and the fittest individual, which is defined as a pseudo-global optimum individual in a population pool. Also, the directionality of the random variation has been exploited to improve the probability of getting better solutions. In addition to this, the importance of initial search width for generating the offspring has been established empirically. The effectiveness of the proposed algorithm has been verified on well-established test functions.","PeriodicalId":218136,"journal":{"name":"Proceedings of the 2000 Congress on Evolutionary Computation. CEC00 (Cat. No.00TH8512)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129234768","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: 56

Convergence properties of some multi-objective evolutionary algorithms 一些多目标进化算法的收敛性

Proceedings of the 2000 Congress on Evolutionary Computation. CEC00 (Cat. No.00TH8512) Pub Date : 2000-07-16 DOI: 10.1109/CEC.2000.870756

G. Rudolph, Alexandru Agapie

引用次数: 247