Table of Contents

• On neutral networks and evolvabilityMarc Ebner, Patrick Langguth, Jürgen Albert, Mark Shackleton, Rob Shipman. 1-8 [doi]
• Not measuring evolvability: initial investigation of an evolutionary robotics search spaceTom Smith, Phil Husbands, Michael O'Shea. 9-16 [doi]
• Evolutionary dynamics of evolutionary programming in noisy environmentYoshiyuki Matsumura, Kazuhiro Ohkura, Kanji Ueda. 17-24 [doi]
• Extrema selection: accelerated evolution on neutral networksTerry Stewart. 25-29 [doi]
• Netcrawling-optimal evolutionary search with neutral networksLionel C. Barnett. 30-37 [doi]
• Automatic selection of sub-populations and minimal spanning distances for improved numerical optimizationJames A. Rumpler, Frank W. Moore. 38-43 [doi]
• A diversity-control-oriented genetic algorithm (DCGA): performance in function optimizationHisashi Shimodaira. 44-51 [doi]
• Complexity analysis of evaluating distances in the genetic algorithm using species conservationJian Ping Li, Márton E. Balázs, Geoffrey T. Parks, P. John Clarkson. 52-59 [doi]
• A study on non-random mating and varying population size in genetic algorithms using a royal road functionCarlos Fernandes, Agostinho C. Rosa. 60-66 [doi]
• The effect of distance measure in a GA with species conservationMárton E. Balázs, Jianping Li, Geoffrey T. Parks, P. John Clarkson. 67-74 [doi]
• A swarm with an effective information sharing mechanism for unconstrained and constrained single objective optimisation problemsTapabrata Ray, Kim-Meow Liew. 75-80 [doi]
• Particle swarm optimization: developments, applications and resourcesRussell C. Eberhart, Yuhui Shi. 81-86 [doi]
• A particle swarm optimization for reactive power and voltage control in electric power systemsYoshikazu Fukuyama, Hirotaka Yoshida. 87-93 [doi]
• Tracking and optimizing dynamic systems with particle swarmsRussell C. Eberhart, Yuhui Shi. 94-100 [doi]
• Fuzzy adaptive particle swarm optimizationYuhui Shi, Russell C. Eberhart. 101-106 [doi]
• An evolutionary active-vision systemToshifumi Kato, Dario Floreano. 107-114 [doi]
• Evolutionary robotics for quasi-ecosystemNaoyuki Kubota, Masanori Mihara, Fumio Kojima. 115-120 [doi]
• Evolutionary algorithm based neural network controller optimization for autonomous mobile robot navigationSeong-Joo Han, Se-Young Oh. 121-127 [doi]
• A comparison of approaches to the evolution of homogeneous multi-robot teamsMatt Quinn. 128-135 [doi]
• Neutral networks in an evolutionary robotics search spaceTom Smith, Phil Husbands, Michael O'Shea. 136-143 [doi]
• Evolving quantum circuits using genetic programmingBenjamin I. P. Rubinstein. 144-151 [doi]
• Control system design unification and automation-a way forward in CACSD via evolutionary computationT. W. Lee, K. C. Tant, E. F. Khor. 152-161 [doi]
• New trends in evolutionary computationPeter J. Bentley, Timothy G. W. Gordon, Jungwon Kim, Sanjeev Kumar 0002. 162-169 [doi]
• GA automated design and synthesis of analog circuits with practical constraintsCindy Goh, Yun Li 0002. 170-177 [doi]
• Maximizing functional test coverage in ASICs using evolutionary algorithmsBurcin Aktan, Molly H. Shor, Garrison W. Greenwood, P. Doyle. 178-182 [doi]
• A new adaptive Boltzmann selection schedule SDSThilo Mahnig, Heinz Mühlenbein. 183-190 [doi]
• Monte Carlo simulation and population-based optimizationAlain Cercueil, Olivier François. 191-198 [doi]
• Optimization of fitness functions with non-ordered parameters by genetic algorithmsAnna L. Buczak, Henry (Hui) Wang. 199-206 [doi]
• MBO: marriage in honey bees optimization-a Haplometrosis polygynous swarming approachHussein A. Abbass. 207-214 [doi]
• Dynamic Niche Clustering: a fuzzy variable radius niching technique for multimodal optimisation in GAsJustin Gan, Kevin Warwick. 215-222 [doi]
• Problem decomposition-based scalable macro-evolutionary algorithmsTao Xiehuowang Chen. 223-231 [doi]
• Hybrid population-based metaheuristic approaches for the space allocation problemEdmund K. Burke, Peter I. Cowling, J. D. Landa Silva. 232-239 [doi]
• Evolutionary design of neural network tree-integration of decision tree, neural network and GAQiangfu Zhao. 240-244 [doi]
• Evolution and analysis of non-autonomous neural networks for walking: reflexive pattern generatorsJohn C. Gallagher. 245-250 [doi]
• On solving the local minima problem of adaptive learning by using deterministic weight evolution algorithmSin Chun Ng, S. H. Leung 0001. 251-255 [doi]
• Evolving neural networks for Hang Seng stock index forecastYong Liu 0012, Xin Yao 0001. 256-260 [doi]
• Genetic programming in time series modelling: an application to meteorological dataKatya Rodríguez-Vázquez. 261-266 [doi]
• Genetic programming of polynomial harmonic models using the discrete Fourier transformNikolay I. Nikolaev, Hitoshi Iba. 267-274 [doi]
• Evolutionary arbitrage for FTSE-100 index options and futuresSheri Markose, Edward Tsang, Hakan Er, Abdel Salhi. 275-282 [doi]
• Compumetric forecasting of crude oil pricesMak A. Kaboudan. 283-287 [doi]
• An evolutionary algorithm for spatial allocation of fluidpower valves on valve-standTrichy M. Kethara Pasupathy, Jiandong Liu, Robert G. Wilhelm. 288-295 [doi]
• Using evolutionary computation to solve the economic load dispatch problemGiridhar Kumaran, V. S. R. K. Mouly. 296-301 [doi]
• Evolution strategies for the optimization of microdevicesSibylle D. Müller, Ivo F. Sbalzarini, Jens H. Walther, Petros Koumoutsakos. 302-309 [doi]
• A heuristic genetic algorithm for grouping manufacturing cellsChao-Hsien Chu, Chang-Chun Tsai. 310-317 [doi]
• A partial order approach to noisy fitness functionsGünther Rudolph. 318-325 [doi]
• Convergence properties of Bayesian evolutionary algorithms with population size greater than 1Si-Eun Lee, Byoung-Tak Zhang, Arnaud Doucet. 326-331 [doi]
• Investigation of the (μ, λ)-ES in the presence of noiseDirk V. Arnold, Hans-Georg Beyer. 332-339 [doi]
• Three-objective optimization in linguistic function approximationHisao Ishibuchi, Tomoharu Nakaskima. 340-347 [doi]
• Improving genetic search for one-dimensional cellular automata, using heuristics related to their dynamic behavior forecastGina M. B. Oliveira, Pedro P. B. de Oliveira, Nizam Omar. 348-355 [doi]
• On fundamental design of parthenogenetic algorithm for the binary quadratic programming problemKengo Katayama, Hiroyuki Narihisa. 356-363 [doi]
• Learning fuzzy cognitive maps using evolution strategies: a novel schema for modeling and simulating high-level behaviorDimitris E. Koulouriotis, Ioannis E. Diakoulakis, Dimitris M. Emiris. 364-371 [doi]
• Actively searching for committees of RBF networks using Bayesian evolutionary computationJe-Gun Joung, Byoung-Tak Zhang. 372-377 [doi]
• An evolving neural network with the amorphous structureHoon Kang, Sung Hwan Jang. 378-383 [doi]
• Evolving a cooperative population of neural networks by minimizing mutual informationYong Liu 0012, Xin Yao 0001, Qiangfu Zhao, Tetsuya Higuchi. 384-389 [doi]
• Speciated neural networks evolved with fitness sharing techniqueJoon-Hyun Ahn, Sung-Bae Cho. 390-396 [doi]
• Evolution and analysis of mixed mode neural networks for walking: mixed pattern generatorsJohn C. Gallagher. 397-402 [doi]
• Time series perturbation by genetic programmingG. Y. Lee. 403-409 [doi]
• A genetic fuzzy expert system for stock market timingS. S. Lam. 410-417 [doi]
• Evolutionary arbitrage for FTSE-100 index options and futuresSheri Markose, Edward Tsang, Hakan Er, Abdel Salhi. 418-425 [doi]
• Evolutionary segmentation of financial time series into subsequencesTak-Chung Fu, Fu-Lai Chung, Vincent T. Y. Ng, Robert W. P. Luk. 426-430 [doi]
• Optimizing windows layout by applying a genetic algorithmNihar Trivedi, Wei Lai, Zhongwei Zhang. 431-435 [doi]
• Studying the optimal parameter range of values in PADGP by means of real-life problemsFrancisco Fernández 0001, Marco Tomassini. 436-441 [doi]
• A genetic approach to automatic bias generation for biased random instruction generationMrinal Bose, Jongshin Shin, Elizabeth M. Rudnick, Todd Dukes, Magdy Abadir. 442-448 [doi]
• Design of interacting multiple model filters based on evolution strategiesJesús García Herrero, Juan A. Besada, José M. Molina López, Gonzalo de Miguel, Javier Portillo Garcia. 449-456 [doi]
• A graph-based approach to the sorting network problemSung-Soon Choi, Byung Ro Moon. 457-464 [doi]
• Thresholding-a selection operator for noisy ESSandor Markon, Dirk V. Arnold, Thomas Bäck, Thomas Beielstein, Hans-Georg Beyer. 465-472 [doi]
• Integrating adaptive mutations and family competition with differential evolution for flexible ligand dockingJinn-Moon Yang, Jorng-Tzong Horng, Cheng-Yan Kao. 473-480 [doi]
• Spectral analysis via supervised genetic search with application-specific mutationsJanet Taylor, Jem J. Rowland, Douglas B. Kell. 481-486 [doi]
• A statistical selection mechanism of GA for stochastic programming problemsKen-ichi Tokoro. 487-492 [doi]
• Genetic algorithms with entropy-Boltzmann samplingsChang-Yong Lee. 493-500 [doi]
• Improving molecular simulation: a meta optimisation of Monte Carlo parametersBenoît Leblanc, Evelyne Lutton, Bertrand Braunschweig, Hervé Toulhoat. 501-507 [doi]
• Bayesian evolutionary algorithms for continuous function optimizationSoo-Yong Shin, Byoung-Tak Zhang. 508-515 [doi]
• Towards computing the parameters of the simple genetic algorithmRoger Jonsson, Jacek Malec. 516-520 [doi]
• Continuous estimation of distribution algorithms with probabilistic principal component analysisDong-Yeon Cho, Byoung-Tak Zhang. 521-526 [doi]
• Multi-objective evolutionary algorithm with non-stationary search spaceEik Fun Khor, Kay Chen Tan, Tong Heng Lee. 527-535 [doi]
• Multiobjective genetic programming: reducing bloat using SPEA2Stefan Bleuler, Martin Brack, Lothar Thiele, Eckart Zitzler. 536-543 [doi]
• A comparison of encodings and algorithms for multiobjective minimum spanning tree problemsJoshua D. Knowles, David W. Corne. 544-551 [doi]
• Multi-point optimization using GAs and Nash/Stackelberg games for high lift multi-airfoil design in aerodynamicsJiang Feng Wang, Jacques Periaux. 552-559 [doi]
• The energy minimization method: a multiobjective fitness evaluation technique and its application to the production scheduling in a petroleum refineryMayron Rodrigues de Almeida, Silvio Hamacher, Marco Aurélio Cavalcanti Pacheco, Marley M. B. R. Vellasco. 560-567 [doi]
• Evolutionary algorithms with adaptive Levy mutationsChang-Yong Lee, Xin Yao 0001. 568-575 [doi]
• Adaptive encoding for aerodynamic shape optimization using evolution strategiesMarkus Olhofer, Yaochu Jin, Bernhard Sendhoff. 576-583 [doi]
• Mesh optimization for surface approximation using an efficient coarse-to-fine evolutionary algorithmHui-Ling Huang, Shinn-Ying Ho. 584-591 [doi]
• Managing approximate models in evolutionary aerodynamic design optimizationYaochu Jin, Markus Olhofer, Bernhard Sendhoff. 592-599 [doi]
• The advantages of generative grammatical encodings for physical designGregory S. Hornby, Jordan B. Pollack. 600-607 [doi]
• Proposal for a field-evolvable hardware based on a microprocessor incorporated flash memoryYuji Sato. 608-615 [doi]
• Self-repairable EPLDs. II. Advanced self-repairing methodologyChong H. Lee, Marek A. Perkowski, Douglas V. Hall, David S. Jun. 616-623 [doi]
• A hardware implementation of the Compact Genetic AlgorithmChatchawit Aporntewan, Prabhas Chongstitvatana. 624-629 [doi]
• Evolutionary calibration of sensors using genetic programming on evolvable hardwareHo-Sik Seok, Byoung-Tak Zhang. 630-634 [doi]
• Initial evolvability experiments on the CAM-brain machines (CBMs)Hugo de Garis, Andrzej Buller, Leo de Penning, Tomasz Chodakowski, Michael Korkin, Gary Fehr, Derek Decesare. 635-642 [doi]
• A crossover operator using independent component analysis for real-coded genetic algorithmsMasato Takahashi, Hajime Kita. 643-649 [doi]
• A set-oriented genetic algorithm and the knapsack problemSebon Ku, Bogju Lee. 650-654 [doi]
• Extrapolation-directed crossover for real-coded GA: overcoming deceptive phenomena by extrapolative searchJun Sakuma, Shigenobu Kobayashi. 655-662 [doi]
• Some experimental observations of (μ/μ, λ)-evolution strategiesMing Chang, Kazuhiro Ohkura, Kang Ueda. 663-670 [doi]
• Sitting guests at a wedding party: experiments on genetic and evolutionary constrained optimizationMiguel Rocha, Rui Mendes 0001, Paulo Cortez 0001, José Neves 0001. 671-678 [doi]
• A messy genetic algorithm for the vehicle routing problem with time window constraintsKay Chen Tan, Tong Heng Lee, Ke Ou, Loo Hay Lee. 679-686 [doi]
• Constrained parameter optimisation: equality constraintsRobert Hinterding. 687-692 [doi]
• Constrained evolutionary exploration via genetic structure of packet distributionKay Chen Tan, Tong Heng Lee, D. Khoo, Eik Fun Khor. 693-703 [doi]
• Evolvable reasoning hardware: its application to the genome informaticsMoritoshi Yasunaga, Takahiro Tsuzuku, Kentaro Ushiyama, Ikuo Yoshihara, Jung H. Kim. 704-711 [doi]
• Inference of gene regulatory model by genetic algorithmsShin Ando, Hitoshi Iba. 712-719 [doi]
• Inferring a system of differential equations for a gene regulatory network by using genetic programmingErina Sakamoto, Hitoshi Iba. 720-726 [doi]
• Multiple relational graphs mapping using genetic algorithmsK. G. Khoo, Ponnuthurai N. Suganthan. 727-733 [doi]
• A genetic clustering algorithm guided by a descent algorithmG. P. Scott, Davide I. Clark, Tuan Pham. 734-740 [doi]
• Applications of genetic algorithms, geostatistics, and fuzzy c-means clustering to image segmentationTuan D. Pham, Michael Wagner 0004, David Clark. 741-746 [doi]
• Evolution of Fisher's discriminantsAlejandro Sierra. 747-752 [doi]
• Rule extraction by genetic algorithms based on a simplified RBF neural networkXiuju Fu, Lipo Wang. 753-758 [doi]
• An evolutionary multi-objective local selection algorithm for customer targetingYongSeog Kim, W. Nick Street, Filippo Menczer. 759-766 [doi]
• Supervised and unsupervised data mining with an evolutionary algorithmRobert Cattral, Franz Oppacher, Dwight Deugo. 767-774 [doi]
• What should a classifier system learn?Tim Kovacs. 775-782 [doi]
• Dynamic trading strategy learning model using learning classifier systemsBenjamin Penyang Liao, Jiah-Shing Chen. 783-789 [doi]
• An entropy-based adaptive genetic algorithm for learning classification rulesLinyu Yang, Dwi H. Widyantoro, Thomas Ioerger, John Yen. 790-796 [doi]
• Probabilistic logical inference using quantities of DNA strandsYasubumi Sakakibara. 797-804 [doi]
• Interaction, evolution, and intelligenceDina Q. Goldin, David Keil. 805-814 [doi]
• Finding solutions to NP problems: philosophical differences between quantum and evolutionary search algorithmsGarrison W. Greenwood. 815-822 [doi]
• Evolutionary computation as a multi-agent search: a -calculus perspective for its completeness and optimalityEugene Eberbach. 823-830 [doi]
• Parallel clustering system using the methodologies of evolutionary computationsReginald L. Walker. 831-838 [doi]
• Classification and function estimation of protein by using data compression and genetic algorithmsShinhji Chiba, Ken Sugawara, Toshinori Watanabe. 839-844 [doi]
• Evolution strategy applied to global optimization of clusters in gene expression data of DNA microarraysKwonmoo Lee, Ju Han Kim, Tae Su Chung, Byoung-Sun Moon, Hoseung Lee, Isaac S. Kohane. 845-850 [doi]
• An evolutionary programming approach to the simulation of visual attentionFred Stentiford. 851-858 [doi]
• Nonlinear blind source separation using a genetic algorithmYing Tan, Jun Wang 0002. 859-866 [doi]
• Texture detection by genetic programmingMario Koeppen, Xiufen Liu. 867-872 [doi]
• When sharing failsRasmus K. Ursem. 873-879 [doi]
• Visualization of EC landscape to accelerate EC conversion and evaluation of its effectFabio Boschetti, Hideyuki Takagi. 880-886 [doi]
• An efficient genetic algorithm with less fitness evaluation by clusteringHee-Su Kim, Sung-Bae Cho. 887-894 [doi]
• Adaptive control of partial functions in genetic programmingDaryl Essam, Robert Ian (Bob) McKay. 895-901 [doi]
• Genetic programming of polynomial harmonic models using the discrete Fourier transformNikolay I. Nikolaev, Hitoshi Iba. 902-909 [doi]
• Global random optimization by simultaneous perturbation stochastic approximationJohn L. Maryak, Daniel C. Chin. 910-916 [doi]
• TGA: a new integrated approach to evolutionary algorithmsChuan-Kang Ting, Sheng-Tun Li, Chungnan Lee. 917-924 [doi]
• Hybrid constrained simulated annealing and genetic algorithms for nonlinear constrained optimizationBenjamin W. Wah, Yixin Chen. 925-932 [doi]
• Genetic algorithm with search area adaptation for the function optimization and its experimental analysisHiroshi Someya, Masayuki Yamamura. 933-940 [doi]
• Classical sorting embedded in genetic algorithms for improved permutation searchVladimir Estivill-Castro, Rodolfo Torres-Velázquez. 941-948 [doi]
• MEA: a metapopulation evolutionary algorithm for multi-objective optimisation problemsMichael Kirley. 949-956 [doi]
• Failure of Pareto-based MOEAs: does non-dominated really mean near to optimal?Kokolo Ikeda, Hajime Kita, Shigenobu Kobayashi. 957-962 [doi]
• Constraint handling with uncertain and noisy multi-objective evolutionEvan J. Hughes. 963-970 [doi]
• PDE: a Pareto-frontier differential evolution approach for multi-objective optimization problemsHussein A. Abbass, Ruhul A. Sarker, Charles S. Newton. 971-978 [doi]
• Evolutionary algorithms for multi-objective optimization: performance assessments and comparisonsKay Chen Tan, Tong Heng Lee, Eik Fun Khor. 979-986 [doi]
• Why more choices cause less cooperation in iterated prisoner's dilemmaPaul J. Darwen, Xin Yao 0001. 987-994 [doi]
• An evolutionary approach for the tuning of a chess evaluation function using population dynamicsGraham Kendall, Glenn Whitwell. 995-1002 [doi]
• Why co-evolution beats temporal difference learning at Backgammon for a linear architecture, but not a non-linear architecturePaul J. Darwen. 1003-1010 [doi]
• Effect of localized selection on the evolution of unplanned coordination in a market selection gameHisao Ishibuchi, Ryoji Sakamoto, Tomoharu Nakashima. 1011-1018 [doi]
• Learning to focus selectively on possible lines of play in checkersThomas M. English. 1019-1024 [doi]
• Evolving bipedal locomotion with genetic programming - a preliminary reportSooyol Ok, Kazuo Miyashita, Kazunori Hase. 1025-1032 [doi]
• Robust controller design with genetic algorithm for flexible spacecraftSam S. Ge, Tong Heng Lee, Fan Hong. 1033-1039 [doi]
• Application of evolutionary computation to aircraft control law designFelix O. Heimes, William S. Ford II, Walker Land Jr.. 1040-1046 [doi]
• Observational emergence of a fuzzy controller evolved by genetic algorithmSeung-Ik Lee, Sung-Bae Cho. 1047-1054 [doi]
• An application of genetic algorithm for designing a Wiener-model controller to regulate the pH value in a pilot plantWoei-Wan Tan, Fengwei Lu, Ai-Poh Loh. 1055-1061 [doi]
• Exact GP schema theory for headless chicken crossover and subtree mutationRiccardo Poli, Nicholas Freitag McPhee. 1062-1069 [doi]
• Representing classification problems in genetic programmingThomas Loveard, Victor Ciesielski. 1070-1077 [doi]
• A schema theory analysis of mutation size biases in genetic programming with linear representationsNicholas Freitag McPhee, Riccardo Poli, Jonathan E. Rowe. 1078-1085 [doi]
• Niche evolution strategy for global optimizationB. Porter, F. Xue. 1086-1092 [doi]
• Team model and taught-by-the-best operationTetsuyuki Takahama, Setsuko Sakai. 1093-1100 [doi]
• Scaling up fast evolutionary programming with cooperative coevolutionYong Liu 0012, Xin Yao, Qiangfu Zhao, Tetsuya Higuchi. 1101-1108 [doi]
• Co-evolution in social interactionsHiroshi Sato, Akira Namatame. 1109-1114 [doi]
• A fuzzy simulated evolution algorithm for the driver scheduling problemJingpeng Li, Raymond S. K. Kwan. 1115-1122 [doi]
• Genetic algorithm with the constraints for nurse scheduling problemHiroharu Kawanaka, Kosuke Yamamoto, Tomohiro Yoshikawa, Tsuyoshi Shinogi, Shinji Tsuruoka. 1123-1130 [doi]
• Collaborative evolutionary multi-project resource schedulingMark Shackelford, David Corne. 1131-1138 [doi]
• Fitness evaluation for nurse scheduling problemsEdmund K. Burke, Patrick De Causmaecker, Sanja Petrovic, Greet Vanden Berghe. 1139-1146 [doi]
• Application of evolutionary computation and neural network hybrids for breast cancer classification using mammogram and history dataWalter H. Land Jr., Timothy Masters, Joseph Y. Lo, Daniel W. McKee. 1147-1154 [doi]
• Self-organized criticality and mass extinction in evolutionary algorithmsThiemo Krink, René Thomsen. 1155-1161 [doi]
• Evolving core promoter signal motifsDavid Corne, Andrew Meade, Richard Sibly. 1162-1169 [doi]
• Using evolutionary algorithms to estimate transition rates of discrete characteristics in phylogenetic treesAndrew Meade, David Corne, Mark Pagel, Richard Sibly. 1170-1176 [doi]
• Learning with the molecular-based hypernetwork modelJose L. Segovia-Juarez, Michael Conrad. 1177-1182 [doi]
• Enzyme genetic programmingMichael A. Lones, Andy M. Tyrrell. 1183-1190 [doi]
• DNA coded GA for the rule base optimization of a fuzzy logic controllerXiao Peng 0009, Prahlad Vadakkepat, Tong Heng Lee. 1191-1196 [doi]
• Using a co-operative co-evolutionary genetic algorithm to solve a three-dimensional container loading problemChaiwat Pimpawat, Nachol Chaiyaratana. 1197-1204 [doi]
• Co-evolutionary computation for constrained min-max problems and its applications for pursuit-evasion gamesJegyom Kim, Min-Jea Tahk. 1205-1212 [doi]
• Coevolutionary GA with schema extraction by machine learning techniques and its application to knapsack problemsHisashi Handa, Tadashi Horiuchi, Osamu Katai, T. Kaneko, Tadataka Konishi, Mitsuru Baba. 1213-1219 [doi]
• Grammars for learning control knowledge with GPRicardo Aler, Daniel Borrajo, Pedro Isasi. 1220-1227 [doi]
• Evolving structure - optimising contentPeter A. Whigham, J. Keukelaar. 1228-1235 [doi]
• Empirical investigations on the genetic adaptive routing algorithm in the InternetMasaharu Munetomo, Naohiko Yamaguchi, Kiyoshi Akama, Yoshiharu Sato. 1236-1243 [doi]
• Towards an artificial immune system for network intrusion detection: an investigation of clonal selection with a negative selection operatorJungwon Kim, Peter J. Bentley. 1244-1252 [doi]
• Evolutionary learning of Web-document structure for information retrievalSun Kim, Byoung-Tak Zhang. 1253-1260 [doi]
• Cooperating search agents explore more than defecting search agents in the Internet information accessJae C. Oh. 1261-1268 [doi]
• A multistage approach to the shortest path on curved surface based on simulated annealing optimizationSi-Dyi Chen, Zhang-Cau Huang, Jiang-Wei Tian. 1269-1275 [doi]
• Comparison between Genetic Network Programming (GNP) and Genetic Programming (GP)Kotaro Hirasawa, M. Okubo, Hiropon Katagiri, J. Hu, J. Murata. 1276-1282 [doi]
• Dynamic traveling salesman problem based on evolutionary computationZhangcan Huang, Xiaolin Hu, Si-Duo Chen. 1283-1288 [doi]
• A GA-based fuzzy traffic simulation for crossroad managementJong-Wan Kim, Byeong Man Kim. 1289-1295 [doi]
• An application of genetic algorithms in smoothing automotive body surfaceZhongwei Zhang, Wei Lui. 1296-1302 [doi]
• Towards evolution of software agents in electronic commerceFangming Zhu, Sheng Uei Guan. 1303-1308 [doi]
• Genetic algorithms for capacity planning of IP-based networksT. T. Mai Hoang, Werner Zorn. 1309-1315 [doi]
• Study of population diversity of multiobjective evolutionary algorithm based on immune and entropy principlesXunxue Cui, Miao Li, Tingjian Fang. 1316-1321 [doi]
• The effects of inactivation of rules for knowledge acquisitionKosuke Yamamoto, Hiroharu Kawanaka, Tomohiro Yoshikawa, Tsuyoshi Shinogi, Shinji Tsuruoka. 1322-1326 [doi]
• An efficient evolutionary image segmentation algorithmShinn-Ying Ho, Kual-Zheng Lee. 1327-1334 [doi]
• Dynamic optimisation of evolving connectionist system training parameters by pseudo-evolution strategyMichael J. Watts, Nikola K. Kasabov. 1335-1342 [doi]
• An adaptive evolutional neuro learning method using genetic search and extraction of rules from trained networksTakumi Ichimura, Shinichi Oeda, Katsumi Yoshida. 1343-1350 [doi]
• Parental population sizing in evolutionary strategiesTao-Yuan Huang, Yung-Yaw Chen. 1351-1358 [doi]
• Differentiation and factor analysis on EDI usage data with an artificial neuromolecular systemJong-Chen Chen, Kwoting Fang. 1359-1365 [doi]
• Evolutionary dynamics of population statesArtur Chorazyczewski, Roman Galar. 1366-1373 [doi]
• Survival of the sickest: a site-specific recombination operator for accelerated function optimizationStephen Drake, Phil Husbands. 1374-1381 [doi]
• A computational study of using genetic algorithms to develop intelligent decision treesZhiwei Fu, Fannie Mae. 1382-1387 [doi]
• Modified Mendel operation for multimodal function optimizationChang Su Park, Hungu Lee, Hyo-choong Bang, Min-Jea Tahk. 1388-1392 [doi]
• An effective dynamic weighted rule for ant colony system optimizationSeungGwan Lee, TaeUng Jung, TaeChoong Chung. 1393-1397 [doi]
• Heuristic operators, redundant mapping and other issues in genetic algorithmsYong Xu, Shen-Chu Xu. 1398-1405 [doi]
• Co-evolutionary optimization of three-dimensional target evasive maneuver against a proportionally guided missileHan-Lim Choi, Hyo-choong Bang, Min-Jea Tahk. 1406-1413 [doi]
• Coordination of multiple behavior modules evolved on CAM-BrainKyung-Joong Kim, Sung-Bae Cho. 1414-1421 [doi]
• Parallel quantum-inspired genetic algorithm for combinatorial optimization problemKuk-Hyun Han, Kui-Hong Park, Ci-Ho Lee, Jong-Hwan Kim 0001. 1422-1429 [doi]
• Hammerstein model identification method based on genetic programmingToshiharu Hatanaka, Katsuji Uosaki. 1430-1435 [doi]
• Hybrid parallel, evolutionary algorithms for constrained optimization utilizing PC clusteringChi-Ho Lee, Kui-Hong Park, Jong-Hwan Kim 0001. 1436-1441 [doi]