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Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97)最新文献

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Herby: an evolutionary artificial ecology Herby:一个进化的人工生态
Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97) Pub Date : 1997-04-13 DOI: 10.1109/ICEC.1997.592328
P. Devine, R. Paton
{"title":"Herby: an evolutionary artificial ecology","authors":"P. Devine, R. Paton","doi":"10.1109/ICEC.1997.592328","DOIUrl":"https://doi.org/10.1109/ICEC.1997.592328","url":null,"abstract":"The paper outlines the design and implementation of an artificial ecology for the investigation of hypotheses relating to real ecologies. An individual based model is used where the differences between individuals provide the basis for selection.","PeriodicalId":167852,"journal":{"name":"Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1997-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133693939","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
EditEr: a combination of IEA and CEA 编者:IEA和CEA的结合
Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97) Pub Date : 1997-04-13 DOI: 10.1109/ICEC.1997.592391
Qiangfu Zhao
{"title":"EditEr: a combination of IEA and CEA","authors":"Qiangfu Zhao","doi":"10.1109/ICEC.1997.592391","DOIUrl":"https://doi.org/10.1109/ICEC.1997.592391","url":null,"abstract":"This paper studies the evolutionary learning of neural networks that can be decomposed into many homogeneous modules, and proposes a new algorithm by combining the individual evolutionary algorithm (IEA) and the co-evolutionary algorithm (CEA). The proposed algorithm has two parts. The first part, a modified version of the IEA, consists of four basic operations: evaluation, deletion, insertion and training. This part is to construct the system using as less modules as possible. The second part is CEA, and the purpose of this part is to evaluate and reproduce good candidate modules for constructing the system. The algorithm is called EditEr in this paper. In the EditEr, an individual is assigned to each module, and the fitness of an individual is defined according to its contribution to the system; a population is assigned to each class of individuals, and many individuals are to be found from each population. Some experimental results are provided to show the efficiency of the EditEr.","PeriodicalId":167852,"journal":{"name":"Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97)","volume":"93 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1997-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115609399","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: 8
Application of an evolution strategy to the Hopfield model of associative memory 进化策略在联想记忆Hopfield模型中的应用
Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97) Pub Date : 1997-04-13 DOI: 10.1109/ICEC.1997.592402
A. Imada, K. Araki
{"title":"Application of an evolution strategy to the Hopfield model of associative memory","authors":"A. Imada, K. Araki","doi":"10.1109/ICEC.1997.592402","DOIUrl":"https://doi.org/10.1109/ICEC.1997.592402","url":null,"abstract":"We apply evolutionary computations to Hopfield's neural network model of associative memory. In the Hopfield model, an almost infinite number of combinations of synaptic weights gives a network an associative memory function. Furthermore, there is a trade-off between the storage capacity and the size of the basin of attraction. Therefore, the model can be thought of as a test suite of multi-modal and/or multi-objective function optimizations. As a preliminary stage, we investigate the basic behavior of an associative memory under simple evolutionary processes. In this paper, we present some experiments using an evolution strategy.","PeriodicalId":167852,"journal":{"name":"Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1997-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115734474","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: 16
A multi-layer detailed routing approach based on evolutionary algorithms 一种基于进化算法的多层详细路由方法
Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97) Pub Date : 1997-04-13 DOI: 10.1109/ICEC.1997.592373
N. Gockel, R. Drechsler, B. Becker
{"title":"A multi-layer detailed routing approach based on evolutionary algorithms","authors":"N. Gockel, R. Drechsler, B. Becker","doi":"10.1109/ICEC.1997.592373","DOIUrl":"https://doi.org/10.1109/ICEC.1997.592373","url":null,"abstract":"We present an evolutionary algorithm (EA) for detailed routing problems (DRPs), like the channel routing problem and the switchbox routing problem. We combine EAs with domain specific knowledge, i.e. the genetic operators make use of the rip-up and reroute technique. The algorithm can work with two layer and multilayer problem instances. The efficiency of our algorithm is demonstrated by application to multilayer channel routing benchmarks. Instances with up to five layers, 130 columns, and more than 60 nets are considered.","PeriodicalId":167852,"journal":{"name":"Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1997-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131074352","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
Influencing parameters of evolutionary algorithms for sequencing problems 排序问题进化算法的影响参数
Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97) Pub Date : 1997-04-13 DOI: 10.1109/ICEC.1997.592376
N. Gockel, R. Drechsler
{"title":"Influencing parameters of evolutionary algorithms for sequencing problems","authors":"N. Gockel, R. Drechsler","doi":"10.1109/ICEC.1997.592376","DOIUrl":"https://doi.org/10.1109/ICEC.1997.592376","url":null,"abstract":"Several problems in computer aided design (CAD) of integrated circuits (ICs) have to solve sequencing problems. For this reason many algorithms for solving these problems have been proposed. Especially, evolutionary algorithms (EAs) have been successfully applied in the past in these areas. We study the influence of different parameters on run time and quality for one specific problem of large practical importance for CAD of ICs, i.e. finding the optimal variable ordering of ordered binary decision diagrams (OBDDs). We consider different genetic operators and a problem specific heuristic. Our study shows that the influence of problem specific knowledge is much more significant than fine tuning the EA, especially if runtime is also considered as an optimization criterion. Our results directly transfer to other sequencing problems.","PeriodicalId":167852,"journal":{"name":"Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1997-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125526489","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: 6
Genetic design of analog IIR filters with variable time delays for optically controlled microwave signal processors 光控微波信号处理器可变时延模拟IIR滤波器的遗传设计
Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97) Pub Date : 1997-04-13 DOI: 10.1109/ICEC.1997.592351
And Neubauer
{"title":"Genetic design of analog IIR filters with variable time delays for optically controlled microwave signal processors","authors":"And Neubauer","doi":"10.1109/ICEC.1997.592351","DOIUrl":"https://doi.org/10.1109/ICEC.1997.592351","url":null,"abstract":"This paper presents the application of genetic algorithms to the design of analog IIR filters with variable time delays-specific examples for tunable optically controlled microwave signal processors. In addition to the IIR filter coefficients as the standard design parameters, the time delays can be optimized. Because of physical constraints, specific restrictions of the design parameters, however, have to be obeyed. In order to make use of the additional freedom of variable time delays and to fulfil the design restrictions, non-standard design procedures are needed. To this end, the applicability of several variants of genetic algorithms to analog IIR filter design is studied. Experimental results and a comparison to standard design techniques are given that demonstrate the excellent properties of the genetic design methodology.","PeriodicalId":167852,"journal":{"name":"Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97)","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1997-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124765216","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
MAX-MIN Ant System and local search for the traveling salesman problem 旅行商问题的最大最小蚂蚁系统与局部搜索
Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97) Pub Date : 1997-04-13 DOI: 10.1109/ICEC.1997.592327
T. Stützle, H. Hoos
{"title":"MAX-MIN Ant System and local search for the traveling salesman problem","authors":"T. Stützle, H. Hoos","doi":"10.1109/ICEC.1997.592327","DOIUrl":"https://doi.org/10.1109/ICEC.1997.592327","url":null,"abstract":"Ant System is a general purpose algorithm inspired by the study of the behavior of ant colonies. It is based on a cooperative search paradigm that is applicable to the solution of combinatorial optimization problems. We introduce MAX-MIN Ant System, an improved version of basic Ant System, and report our results for its application to symmetric and asymmetric instances of the well known traveling salesman problem. We show how MAX-MIN Ant System can be significantly improved, extending it with local search heuristics. Our results clearly show that MAX-MIN Ant System has the property of effectively guiding the local search heuristics towards promising regions of the search space by generating good initial tours.","PeriodicalId":167852,"journal":{"name":"Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97)","volume":"170 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1997-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122991730","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: 930
A scatter search based approach for the quadratic assignment problem 基于散点搜索的二次分配问题求解方法
Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97) Pub Date : 1997-04-13 DOI: 10.1109/ICEC.1997.592289
V. Cung, T. Mautor, P. Michelon, A. Tavares
{"title":"A scatter search based approach for the quadratic assignment problem","authors":"V. Cung, T. Mautor, P. Michelon, A. Tavares","doi":"10.1109/ICEC.1997.592289","DOIUrl":"https://doi.org/10.1109/ICEC.1997.592289","url":null,"abstract":"Scatter search is an evolutionary heuristic, proposed two decades ago, that uses linear combinations of a population subset to create new solutions. A special operator is used to ensure their feasibility and to improve their quality. The authors propose a scatter search approach to the QAP problem. The basic method is extended with intensification and diversification stages and they present a procedure to generate good scattered initial solutions.","PeriodicalId":167852,"journal":{"name":"Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97)","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1997-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121488894","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: 122
Fuzzy goal programming using genetic algorithm 基于遗传算法的模糊目标规划
Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97) Pub Date : 1997-04-13 DOI: 10.1109/ICEC.1997.592345
M. Gen, K. Ida, Jae Hyun Kim
{"title":"Fuzzy goal programming using genetic algorithm","authors":"M. Gen, K. Ida, Jae Hyun Kim","doi":"10.1109/ICEC.1997.592345","DOIUrl":"https://doi.org/10.1109/ICEC.1997.592345","url":null,"abstract":"Goal programming is a powerful method which involves multiobjectives and is one of the excellent model in many real-world problems. The goal programming is to establish specific goals for each priority level, formulate objective functions for each objective, and then seek a solution that minimize the deviations of these objective functions from their respective goals. Often, in real-world problems the objectives are imprecise (or fuzzy). Recently, genetic algorithms are used to solve many real-world problems and have received a great deal of attention about their ability as optimization techniques for multiobjective optimization problems. This paper is attempt to apply these genetic algorithms to the goal programming problems which involve imprecise (or fuzzy) nonlinear information. Finally, we try to get some numerical experiments which have multiobjectives, and imprecise nonlinear information, using goal programming and genetic algorithm.","PeriodicalId":167852,"journal":{"name":"Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1997-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131817803","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: 6
A simplex genetic algorithm hybrid 一种单纯形混合遗传算法
Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97) Pub Date : 1997-04-13 DOI: 10.1109/ICEC.1997.592291
J. Yen, B. Lee
{"title":"A simplex genetic algorithm hybrid","authors":"J. Yen, B. Lee","doi":"10.1109/ICEC.1997.592291","DOIUrl":"https://doi.org/10.1109/ICEC.1997.592291","url":null,"abstract":"One of the main obstacles in applying genetic algorithms (GAs) to complex problems has been the high computational cost due to their slow convergence rate. To alleviate this difficulty, we developed a hybrid approach that combines a GA with a stochastic variant of the simplex method in function optimization. Our motivation for developing the stochastic simplex method is to introduce a cost-effective exploration component into the conventional simplex method. In an attempt to make effective use of the simplex operation in a hybrid GA framework, we used an elite-based hybrid architecture that applies one simplex step to a top portion of the ranked population. We compared our approach with five alternative optimization techniques, including another simplex-GA hybrid, developed independently by Renders and Bersini (1994), and adaptive simulated annealing (ASA). We used two function optimization problems to compare our approach with the five alternative methods. Overall, these tests showed that our hybrid approach is an effective and robust optimization technique. We also tested our hybrid GA on the seven function benchmark problems on real space and showed its results.","PeriodicalId":167852,"journal":{"name":"Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97)","volume":"199 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1997-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131408492","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: 40
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