Volume 8, Number 1, February 2004

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  Chang-Yong Lee, Xin Yao: Evolutionary programming using mutations based on the Levy probability distribution. 1-13
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  Lourdes Araujo: Symbiosis of evolutionary techniques and statistical natural language processing. 14-27
• 
  Martin V. Butz, Tim Kovacs, Pier Luca Lanzi, Stewart W. Wilson: Toward a theory of generalization and learning in XCS. 28-46
• 
  Edmund K. Burke, Steven Gustafson, Graham Kendall: Diversity in genetic programming: an analysis of measures and correlation with fitness. 47-62
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  Adam Prügel-Bennett: Symmetry breaking in population-based optimization. 63-79
• 
  Qingfu Zhang: On stability of fixed points of limit models of univariate marginal distribution algorithm and factorized distribution algorithm. 80-93

Volume 8, Number 2 April 2004

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  Yew-Soon Ong, Andy J. Keane: Meta-Lamarckian learning in memetic algorithms. 99-110
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  John C. Gallagher, Saranyan Vigraham, Gregory R. Kramer: A family of compact genetic algorithms for intrinsic evolvable hardware. 111-126
• 
  Qingfu Zhang, Heinz Mühlenbein: On the convergence of a class of estimation of distribution algorithms. 127-136
• 
  Neal K. Bambha, Shuvra S. Bhattacharyya, Jürgen Teich, Eckart Zitzler: Systematic integration of parameterized local search into evolutionary algorithms. 137-155
• 
  Kuk-Hyun Han, Jong-Hwan Kim: Quantum-inspired evolutionary algorithms with a new termination criterion, H_epsilon gate, and two-phase scheme. 156-169
• 
  Marco Laumanns, Lothar Thiele, Eckart Zitzler: Running time analysis of multiobjective evolutionary algorithms on pseudo-Boolean functions. 170-182
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  Durga Prasad Muni, Nikhil R. Pal, Jyotirmay Das: A novel approach to design classifiers using genetic programming. 183-196

Volume 8, Number 3, June 2004

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  Russell C. Eberhart, Yuhui Shi: Guest Editorial Special Issue on Particle Swarm Optimization. 201-203
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  Rui Mendes, James Kennedy, José Neves: The Fully Informed Particle Swarm: Simpler, Maybe Better. 204-210
• 
  Konstantinos E. Parsopoulos, Michael N. Vrahatis: On the Computation of All Global Minimizers Through Particle Swarm Optimization. 211-224
• 
  F. vandenBergh, Andries Petrus Engelbrecht: A Cooperative Approach to Particle Swarm Optimization. 225-239
• 
  Asanga Ratnaweera, Saman K. Halgamuge, Harry C. Watson: Self-Organizing Hierarchical Particle Swarm Optimizer With Time-Varying Acceleration Coefficients. 240-255
• 
  Carlos A. Coello Coello, Gregorio Toscano Pulido, M. Salazar Lechuga: Handling Multiple Objectives With Particle Swarm Optimization. 256-279
• 
  L. Messerschmidt, Andries Petrus Engelbrecht: Learning to Play Games Using a PSO-Based Competitive Learning Approach. 280-288
• 
  Mark P. Wachowiak, Renata Smolíkova, Yufeng Zheng, Jacek M. Zurada, Adel Said Elmaghraby: An Approach to Multimodal Biomedical Image Registration Utilizing Particle Swarm Optimization. 289-301

Volume 8, Number 4, August 2004

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  You Seok Son, Ross Baldick: Hybrid coevolutionary programming for Nash equilibrium search in games with local optima. 305-315
• 
  Sushil J. Louis, John R. McDonnell: Learning with case-injected genetic algorithms. 316-328
• 
  Giuseppe Ascia, Vincenzo Catania, Maurizio Palesi: A GA-based design space exploration framework for parameterized system-on-a-chip platforms. 329-346
• 
  Francesco Cupertino, Ernesto Mininno, David Naso, Biagio Turchiano, Luigi Salvatore: On-line genetic design of anti-windup unstructured controllers for electric drives with variable load. 347-364
• 
  Jinn-Tsong Tsai, Tung-Kuan Liu, Jyh-Horng Chou: Hybrid Taguchi-genetic algorithm for global numerical optimization. 365-377
• 
  Man Leung Wong, Kwong-Sak Leung: An efficient data mining method for learning Bayesian networks using an evolutionary algorithm-based hybrid approach. 378-404
• 
  Andrew Czarn, Cara MacNish, Kaipillil Vijayan, Berwin A. Turlach, Ritu Gupta: Statistical exploratory analysis of genetic algorithms. 405-421
• 
  Ant Colony Optimization. 422-423

Volume 8, Number 5, October 2004

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  Marco Farina, Kalyanmoy Deb, Paolo Amato: Dynamic multiobjective optimization problems: test cases, approximations, and applications. 425-442
• 
  Assaf Zaritsky, Moshe Sipper: The preservation of favored building blocks in the struggle for fitness: the puzzle algorithm. 443-455
• 
  Zhenguo Tu, Yong Lu: A robust stochastic genetic algorithm (StGA) for global numerical optimization. 456-470
• 
  Fu-Lai Chung, Tak-Chung Fu, Vincent T. Y. Ng, Robert W. P. Luk: An evolutionary approach to pattern-based time series segmentation. 471-489
• 
  Rommel G. Regis, Christine A. Shoemaker: Local function approximation in evolutionary algorithms for the optimization of costly functions. 490-505
• 
  Franck Robin, Esteban Moreno Soriano: Analysis of fitness functions for electron-beam lithography simulation and evolutionary optimization. 506-511

Volume 8, Number 6, December 2004

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  Minaya Villasana, Gabriela Ochoa: Heuristic design of cancer chemotherapies. 513-521
• 
  Shinn-Ying Ho, Li-Sun Shu, Jian-Hung Chen: Intelligent evolutionary algorithms for large parameter optimization problems. 522-541
• 
  Yun-Seog Yeun, Won-Sun Ruy, Young-Soon Yang, Nam-Joon Kim: Implementing linear models in genetic programming. 542-566
• 
  Xiao Wang, Han Wang: Evolutionary optimization with Markov random field prior. 567-579
• 
  Antonio Della Cioppa, Claudio De Stefano, Angelo Marcelli: On the role of population size and niche radius in fitness sharing. 580-592
• 
  Taghi M. Khoshgoftaar, Yi Liu, Naeem Seliya: A multiobjective module-order model for software quality enhancement. 593-608

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