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

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Random keys genetic algorithm with adaptive penalty function for optimization of constrained facility layout problems 带自适应惩罚函数的随机密钥遗传算法求解受限设施布局优化问题
Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97) Pub Date : 1997-04-13 DOI: 10.1109/ICEC.1997.592258
B. Norman, A.E. Smith
{"title":"Random keys genetic algorithm with adaptive penalty function for optimization of constrained facility layout problems","authors":"B. Norman, A.E. Smith","doi":"10.1109/ICEC.1997.592258","DOIUrl":"https://doi.org/10.1109/ICEC.1997.592258","url":null,"abstract":"This paper presents an extended formulation of the unequal area facilities block layout problem which explicitly considers uncertainty in material handling costs by use of expected value and standard deviations of product forecasts. This formulation is solved using a random keys genetic algorithm (RKGA) to circumvent the need for repair operators after crossover and mutation. Because this problem can be highly constrained depending on the maximum allowable aspect ratios of the facility departments, an adaptive penalty function is used to guide the search to feasible, but not suboptimal, regions. The RKGA is shown to be a robust optimizer which allows a user to make an explicit characterization of the cost and uncertainty trade-offs involved in a particular block layout problem.","PeriodicalId":167852,"journal":{"name":"Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97)","volume":"509 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":"116981874","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: 35
The importance of maintaining behavioural link between parents and offspring 保持父母和后代之间行为联系的重要性
Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97) Pub Date : 1997-04-13 DOI: 10.1109/ICEC.1997.592388
X. Yao
{"title":"The importance of maintaining behavioural link between parents and offspring","authors":"X. Yao","doi":"10.1109/ICEC.1997.592388","DOIUrl":"https://doi.org/10.1109/ICEC.1997.592388","url":null,"abstract":"In a study of evolutionary artificial neural networks (Yao and Liu, 1996), it has been argued that a partial training process after an architectural mutation plays an important role in maintaining the behavioural link between parents and their offspring and thus is beneficial to the simulated evolution. This paper investigates the issue further through a number of experiments. The experimental results show that a closer behavioural link between parents and their offspring due to the partial training process does lead to better performance, i.e., evolved ANNs generalise better. The results also illustrate that given a fixed amount of time there is an optimal balance of time between evolution and training (learning).","PeriodicalId":167852,"journal":{"name":"Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97)","volume":"51 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":"132248970","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: 14
Evolutionary transition on Virus-Evolutionary Genetic Algorithm 病毒-进化遗传算法的进化过渡
Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97) Pub Date : 1997-04-13 DOI: 10.1109/ICEC.1997.592320
N. Kubota, T. Fukuda, T. Arakawa, K. Shimojima
{"title":"Evolutionary transition on Virus-Evolutionary Genetic Algorithm","authors":"N. Kubota, T. Fukuda, T. Arakawa, K. Shimojima","doi":"10.1109/ICEC.1997.592320","DOIUrl":"https://doi.org/10.1109/ICEC.1997.592320","url":null,"abstract":"The paper deals with a genetic algorithm (GA) based on the virus theory of evolution (VEGA) and evolutionary transition of a population. VEGA can self adaptively change the searching ratio between local search and global search according to the current state of population of candidate solutions. In addition, various types of evolutionary optimization methods have been proposed and successfully applied to many optimization problems. However, it is difficult to determine the coding method, genetic operators and selection scheme. To analyze the behavior of GAs, Markov chain analysis, deceptive problems and schema analysis have been discussed. We discuss evolutionary transition concerning fitness improvement through numerical simulation of the traveling salesman problem. The simulation results indicate that particular genetic operators give a population different potentialities for generating candidate solutions and that virus infection operators can generate effective schemata and propagate them to a population evolved with any genetic operators.","PeriodicalId":167852,"journal":{"name":"Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97)","volume":"100 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":"134613988","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: 18
On the power of circular splicing systems and DNA computability 关于环状剪接系统和DNA可计算性的能力
Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97) Pub Date : 1997-04-13 DOI: 10.1109/ICEC.1997.592299
T. Yokomori, S. Kobayashi, Claudio Ferretti
{"title":"On the power of circular splicing systems and DNA computability","authors":"T. Yokomori, S. Kobayashi, Claudio Ferretti","doi":"10.1109/ICEC.1997.592299","DOIUrl":"https://doi.org/10.1109/ICEC.1997.592299","url":null,"abstract":"From a biological motivation of the interactions between linear and circular DNA sequences, we propose a new type of splicing model called \"circular H systems\" and show that they have the same computational power as Turing machines. It is also shown that there effectively exists a universal circular H system which can simulate any circular H system with the same terminal alphabet, which strongly suggests a feasible design for a DNA computer based on circular splicing.","PeriodicalId":167852,"journal":{"name":"Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97)","volume":"21 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":"131708122","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
AdAM: a hardware evolutionary system 亚当:硬件进化系统
Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97) Pub Date : 1997-04-13 DOI: 10.1109/ICEC.1997.592294
H. Hemmi, T. Hikage, K. Shimohara
{"title":"AdAM: a hardware evolutionary system","authors":"H. Hemmi, T. Hikage, K. Shimohara","doi":"10.1109/ICEC.1997.592294","DOIUrl":"https://doi.org/10.1109/ICEC.1997.592294","url":null,"abstract":"AdAM (Adaptive Architecture Methodology) is a hardware evolutionary system making electronic circuits autonomously acquire required functionalities. Among the systems aiming for this same goal, this system is unique in building up a system-oriented methodology rather than a device-oriented technique; AdAM is designed to be a high-level behavior-oriented evolutionary system framework with an extremely high operation/evolution speed. This paper overviews the architecture of the AdAM system and investigates the methodology used in the system. Some research projects based on AdAM are also presented.","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":"131751640","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: 20
Automated television scheduling via evolving agents 通过进化代理实现的自动电视调度
Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97) Pub Date : 1997-04-13 DOI: 10.1109/ICEC.1997.592407
W. Lin, R. N. Bernard, G. Janes, K.W. Farrell
{"title":"Automated television scheduling via evolving agents","authors":"W. Lin, R. N. Bernard, G. Janes, K.W. Farrell","doi":"10.1109/ICEC.1997.592407","DOIUrl":"https://doi.org/10.1109/ICEC.1997.592407","url":null,"abstract":"Presents a novel method of incorporating agent methodology, genetic algorithms and game theory to analyze television scheduling. We designed the three major United States networks as autonomous agents that compete for viewership of a population of household agents. In a competitive environment, these network agents attempt to maximize their ratings by evaluating other network agents' behaviors and schedules. They then evolve their schedule via a genetic algorithm to better compete for viewers. Viewer agents choose activities that maximize their satisfaction. The richness of this simulation provides insight into the seemingly impenetrable dynamic environment of television scheduling.","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":"127704512","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: 4
Knowledge-based self-adaptation in evolutionary programming using cultural algorithms 基于知识的基于文化算法的进化规划自适应
Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97) Pub Date : 1997-04-13 DOI: 10.1109/ICEC.1997.592271
R. Reynolds, C. Chung
{"title":"Knowledge-based self-adaptation in evolutionary programming using cultural algorithms","authors":"R. Reynolds, C. Chung","doi":"10.1109/ICEC.1997.592271","DOIUrl":"https://doi.org/10.1109/ICEC.1997.592271","url":null,"abstract":"We investigate knowledge-based self-adaptation in evolutionary programming (EP) using cultural algorithms for 22 function optimization problems. The results suggest that the use of a cultural framework for self-adaptation in EP can produce substantial performance improvements as expressed in terms of CPU time. The nature of these improvements and the type of knowledge that is most effective in producing them will depend on the structure of the problem.","PeriodicalId":167852,"journal":{"name":"Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97)","volume":"33 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":"116747587","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: 66
The emergence of insect protandry: a "natural" evolutionary computation application 昆虫原生体的出现:一个“自然的”进化计算应用
Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97) Pub Date : 1997-04-13 DOI: 10.1109/ICEC.1997.592330
K. Downing
{"title":"The emergence of insect protandry: a \"natural\" evolutionary computation application","authors":"K. Downing","doi":"10.1109/ICEC.1997.592330","DOIUrl":"https://doi.org/10.1109/ICEC.1997.592330","url":null,"abstract":"When resources and their consumers have matching distributions in space or time, an ideal free distribution (IFD) is achieved, whereby each consumer receives the same amount of resource. In nature, both spatial and temporal IFDs are commonplace, with protandry in insects providing a popular textbook example of the latter. This research uses individual based population models and genetic algorithms to simulate the emergence of both general temporal IFDs and insect protandry. The results indicate that evolutionary computation with fitness proportionate reproduction in negative frequency dependent situations (e.g., resource sharing contexts) leads to the rapid emergence of IFDs. Since ideal free distributions constitute implicitly cooperative arrangements among heterogenous strategies competing for a common resource, this work illustrates the ability of simple genetic algorithms to simulate the emergence of organized polymorphic structures rather than a single maximally fit phenotype.","PeriodicalId":167852,"journal":{"name":"Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97)","volume":"30 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":"124866031","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
On the use of niching for dynamic landscapes 论动态景观中生态位的运用
Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97) Pub Date : 1997-04-13 DOI: 10.1109/ICEC.1997.592336
Walter Cedefio, R. Vemuri
{"title":"On the use of niching for dynamic landscapes","authors":"Walter Cedefio, R. Vemuri","doi":"10.1109/ICEC.1997.592336","DOIUrl":"https://doi.org/10.1109/ICEC.1997.592336","url":null,"abstract":"Application of genetic algorithms to problems where the fitness landscape changes dynamically is a challenging problem. Genetic algorithms for such environments must maintain a diverse population that can adapt to the changing landscape and locate better solutions dynamically. A niching genetic algorithm suitable for locating multiple solutions in a multimodal landscape is applied. The results show the suitability of such approach to locate and maintain solutions in a dynamic landscape.","PeriodicalId":167852,"journal":{"name":"Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97)","volume":"92 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":"122755814","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: 105
A new algorithm for DNA based computation 一种基于DNA计算的新算法
Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97) Pub Date : 1997-04-13 DOI: 10.1109/ICEC.1997.592297
R. C. Murphy, R. Deaton, D. Franceschetti, S. E. Stevens, M. Garzon
{"title":"A new algorithm for DNA based computation","authors":"R. C. Murphy, R. Deaton, D. Franceschetti, S. E. Stevens, M. Garzon","doi":"10.1109/ICEC.1997.592297","DOIUrl":"https://doi.org/10.1109/ICEC.1997.592297","url":null,"abstract":"A common feature of DNA computing involves the use of molecular biology techniques to extract molecules representing the solution to a computation from a reaction mixture. Current applied extraction methods often employ PCR (polymerase chain reactions) and/or gel electrophoresis, both of which we believe are too time-consuming and error-prone to yield a practical DNA-based molecular computing capability. This paper suggests a new approach to solving the Hamiltonian graph and similar combinatorial problems that avoids these traditional techniques in favor of a purely enzymatic methodology.","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":"116469815","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
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