Genetic and Evolutionary Computation COnference

GECCO-2005

Table of Contents

Author Index

Ant Colony Optimization and Swarm Intelligence

BeeAdHoc: An Energy Efficient Routing Algorithm for Mobile Ad Hoc Networks Inspired by Bee Behavior  (page 153)
H. F. Wedde, M. Farooq, T. Pannenbaecker, B. Vogel, C. Mueller, 
J. Meth, R. Jeruschkat (University of Dortmund)

Breeding Swarms: A GA/PSO Hybrid  (page 161)
M. Settles, T. Soule (University of Idaho)

Exploring Extended Particle Swarms: A Genetic Programming Approach  (page 169)
R. Poli, C. Di Chio, W. B. Langdon (University of Essex)

Improving Particle Swarm Optimization with Differentially Perturbed Velocity  (page 177)
S. Das, A. Konar (Jadavpur University)
U. K. Chakraborty (University of Missouri)

Breeding Swarms: A New Approach to Recurrent Neural Network Training  (page 185)
M. Settles, P. Nathan, T. Soule (University of Idaho)

Bayesian Optimization Models for Particle Swarms  (page 193)
C. K. Monson, K. D. Seppi (Brigham Young University)

Dynamic-Probabilistic Particle Swarms  (page 201)                    (Return to Top)
J. Kennedy (US Bureau of Labor Statistics)

Constrained Optimization via Particle Evolutionary Swarm Optimization Algorithm (PESO)  (page 209)
A. E. Muñoz Zavala, A. Hernández-Aguirre, E. R. Villa Diharce (Center for Research in Mathematics (CIMAT))

Evolving Agent Swarms for Clustering and Sorting  (page 217)
V. Hartmann (The Norwegian University of Science and Technology (NTNU))

Promising Infeasibility and Multiple Offspring Incorporated to Differential Evolution for Constrained Optimization  (page 225)
E. Mezura-Montes, J. Velázquez-Reyes, C. A. Coello Coello (Evolutionary Computation Group (EVOCINV))

Scale Invariant Pareto Optimality: A Meta—Formalism For Characterizing and Modeling Cooperativity in Evolutionary Systems  (page 233)
M. Fleischer (Johns Hopkins University)

Exposing Origin-Seeking Bias in PSO  (page 241)
C. K. Monson, K. D. Seppi (Brigham Young University)

Ant Colony Optimization for Power Plant Maintenance Scheduling Optimization  (page 249)
W. K. Foong, H. R. Maier, A. R. Simpson (The University of Adelaide)

An Effective Use of Crowding Distance in Multiobjective Particle Swarm Optimization  (page 257)
C. R. Raquel (University of the Philippines-Baguio)
P. C. Naval, Jr. (University of the Phillippines - Dilliman)

Ant Colony Optimization and Swarm Intelligence: Posters

MeSwarm: Memetic Particle Swarm Optimization  (page 267)                    (Return to Top)
B.-F. Liu, H.-M. Chen (Feng Chia University)
J.-H. Chen (Academia Sinica)
S.-F. Hwang (Feng Chia University)
S.-Y. Ho (National Chiao Tung University)

Factors Governing The Behavior of Multiple Cooperating Swarms  (page 269)
M. El-Abd, M. Kamel (University of Waterloo)

Solving Geometric TSP with Ants  (page 271)
T. N. Bui, M. Colpan (The Pennsylvania State University at Harrisburg)

Simulating Swarm Intelligence in Honey Bees: Foraging in Differently Fluctuating Environments (page 273)
T. Schmickl, R. Thenius, K. Crailsheim (Karl-Franzens University Graz)

A Model Based on Ant Colony System and Rough Set 
Theory to Feature Selection  (page 275)
R. Bello (Universidad Central de Las Villas)
A Nowe (Vrije Universiteit)
Y. Caballero (Universidad de Camagüey)
Y. Gómez (Universidad Central de Las Villas)
P. Vrancx (Vrije Universiteit)

A Modified Particle Swarm Optimization Predicted by Velocity  (page 277)
Z. Cui, J. Zeng (University of Science and Technology)