| Evolutionary optimization in spatio-temporal fitness landscapes | p. 1 |
| Cumulative step length adaptation on ridge functions | p. 11 |
| General lower bounds for evolutionary algorithms | p. 21 |
| On the ultimate convergence rates for isotropic algorithms and the best choices among various forms of isotropy | p. 32 |
| Mixed-integer NK landscapes | p. 52 |
| How comma selection helps with the escape from local optima | p. 52 |
| When do heavy-tail distributions help? | p. 62 |
| Self-adaptation on the ridge function class : first results for the sharp ridge | p. 72 |
| Searching for balance : understanding self-adaptation on ridge functions | p. 82 |
| Diversity loss in general estimation of distribution algorithms | p. 92 |
| Information perspective of optimization | p. 102 |
| A novel negative selection algorithm with an array of partial matching lengths for each detector | p. 112 |
| Hierarchical BOA, cluster exact approximation, and ising spin glasses | p. 122 |
| Towards an adaptive multimeme algorithm for parameter optmisation suiting the engineers' needs | p. 132 |
| Niche radius adaptation in the CMA-ES niching algorithm | p. 142 |
| A Tabu search evolutionary algorithm for solving constraint satisfaction problems | p. 152 |
| cAS : ant colony optimization with cunning ants | p. 162 |
| Genetic algorithm based on independent component analysis for global optimization | p. 172 |
| Improved squeaky wheel optimisation for driver scheduling | p. 182 |
| A local genetic algorithm for binary-coded problems | p. 192 |
| Hill climbers and mutational heuristics in hyperheuristics | p. 202 |
| A multi-level memetic/extact hybrid algorithm for the still life problem | p. 212 |
| Transmission loss reduction based on FACTS and bacteria foraging algorithm | p. 222 |
| Substructural neighborhoods for local search in the Bayesian optimization algorithm | p. 232 |
| Theory and practice of cellular UMDA for discrete optimization | p. 242 |
| A memetic approach to golomb rulers | p. 252 |
| Some notes on (mem)brane computation | p. 262 |
| Evolutionary local search for designing peer-to-peer overlay topologies based on minimum routing cost spanning trees | p. 272 |
| Nature-inspired algorithms for the optimization of optical reference signals | p. 282 |
| Optimum design of surface acoustic wave filters based on the Taguchi's quality engineering with a memetic algorithm | p. 292 |
| Genetic algorithm for burst detection and activity tracking in event streams | p. 302 |
| Computationally intelligent online dynamic vehicle routing by explicit load prediction in an evolutionary algorithm | p. 312 |
| Novel approach to develop rheological structure-property relationships using genetic programming | p. 322 |
| An evolutionary approach to the inference of phylogenetic networks | p. 332 |
| An evolutive approach for the delineation of local labour markets | p. 342 |
| Direct manipulation of free form deformation in evolutionary design optimisation | p. 352 |
| An evolutionary approach to shimming undulator magnets for synchrotron radiation sources | p. 362 |
| New EAX crossover for large TSP instances | p. 372 |
| Functional brain imaging with multi-objective multi-modal evolutionary optimization | p. 382 |
| A new neural network based construction heuristic for the examination timetabling problem | p. 392 |
| Optimisation of CDMA-based mobile telephone networks : algorithmic studies on real-world networks | p. 402 |
| Evolving novel and effective treatment plans in the context of infection dynamics models : illustrated with HIV and HAART therapy | p. 413 |
| Automatic test pattern generation with BOA | p. 423 |
| Multiobjective genetic programming for natural language parsing and tagging | p. 433 |
| Modelling the population distribution in multi-objective optimization by generative topographic mapping | p. 443 |
| Multiobjective optimization of ensembles of multilayer perceptrons for pattern classification | p. 453 |
| Multi-objective equivalent random search | p. 463 |
| Compressed-objective genetic algorithm | p. 473 |
| A new proposal for multiobjective optimization using particle swarm optimization and rough sets theory | p. 483 |
| Incorporation of scalarizing fitness functions into evolutionary multiobjective optimization algorithms | p. 493 |
| Solving multi-objective optimisation problems using the potential pareto regions evolutionary algorithm | p. 503 |
| Pareto set and EMOA behavior for simple multimodal multiobjective functions | p. 513 |
| About selecting the personal best in multi-objective particle swarm optimization | p. 523 |
| Are all objectives necessary? : on dimensionality reduction in evolutionary multiobjective optimization | p. 533 |
| Solving hard multiobjective optimization problems using [epsilon]-constraint with cultured differential evolution | p. 543 |
| A fast and effective method for pruning of non-dominated solutions in many-objective problems | p. 553 |
| Multi-level ranking for constrained multi-objective evolutionary optimisation | p. 563 |
| Module identification from heterogeneous biological data using multiobjective evolutionary algorithms | p. 573 |
| A multiobjective differential evolution based on decomposition for multiobjective optimization with variable linkages | p. 583 |
| Digital images enhancement with use of evolving neural networks | p. 593 |
| Environments conducive to evolution of modularity | p. 603 |
| Arms races and car races | p. 613 |
| BeeHiveAIS : a simple, efficient, scalable and secure routing framework inspired by artificial immune systems | p. 623 |
| Critical temperatures for intermittent search in self-organizing neural networks | p. 633 |
| Robust simulation of lamprey tracking | p. 641 |
| Evolutionary behavior acquisition for humanoid robots | p. 651 |
| Modelling group-foraging behaviour with particle swarms | p. 661 |
| Neuroevlution with analog genetic encoding | p. 671 |
| A two-level clustering method using linear linkage encoding | p. 681 |
| A new swarm intelligence coordination model inspired by collective prey retrieval and its application to image alignment | p. 691 |
| Exploring the effect of proximity and kinship on mutual cooperation in the iterated prisoner's dilemma | p. 701 |
| Investigating the emergence of multicellularity using a population of neural network agents | p. 711 |
| Building of 3D environment models for mobile robotics using self-organization | p. 721 |
| January : a parallel algorithm for bug hunting based on insect behavior | p. 731 |
| A generalized graph-based method for engineering swarm solutions to multiagent problems | p. 741 |
| Probabilistic adaptive mapping developmental genetic programming (PAM DGP) : a new developmental approach | p. 751 |
| A distance-based information preservation tree crossover for the maximum parsimony problem | p. 761 |
| Solving SAT and HPP with accepting splicing systems | p. 771 |
| Some steps towards understanding how neutrality affects evolutionary search | p. 778 |
| Performance of evolutionary algorithms on random decomposable problems | p. 788 |
| Evolving binary decision diagrams with emergent variable orderings | p. 798 |
| Life history evolution of virtual plants : trading off between growth and reproduction | p. 808 |
| Finding state-of-the-art non-cryptographic hashes with genetic programming | p. 818 |
| Offspring generation method using delaunay triangulation for real-coded genetic algorithms | p. 828 |
| An investigation of representations and operators for evolutionary data clustering with a variable number of clusters | p. 839 |
| Lamar : a new pseudorandom number generator evolved by means of genetic programming | p. 850 |
| Evolving bin packing heuristics with genetic programming | p. 860 |
| The importance of neutral mutations in GP | p. 870 |
| New order-based crossovers for the graph coloring problem | p. 880 |
| Assortative mating drastically alters the magnitude of error thresholds | p. 890 |
| Is self-adaptation of selection pressure and population size possible? - a case study | p. 900 |
| A particle swarm optimizer for constrained numerical optimization | p. 910 |
| Self-regulated population size in evolutionary algorithms | p. 920 |
| Starting from scratch : growing longest common subsequences with evolution | p. 930 |
| Local meta-models for optimization using evolution strategies | p. 939 |
| Effects of using two neighborhood structures in cellular genetic algorithms for function optimization | p. 949 |
| A selecto-recombinative genetic algorithm with continuous chromosome reconfiguration | p. 959 |
| Exploiting expert knowledge in genetic programming for genome-wide genetic analysis | p. 969 |
| Speeding up evolutionary algorithms through restricted mutation operators | p. 978 |
| Comparing the niches of CMA-ES, CHC and pattern search using diverse benchmarks | p. 988 |
| Model complexity vs. performance in the Bayesian optimization algorithm | p. 998 |
| Genetic programming for kernel-based learning with co-evolving subsets selection | p. 1008 |
| Product geometric crossover | p. 1018 |
| Exploration and exploitation bias of crossover and path relinking for permutation problems | p. 1028 |
| Geometric crossover for sets, multisets and partitions | p. 1038 |
| Ordinal regression in evolutionary computation | p. 1048 |
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