Parallel Problem Solving from Nature - Ppsn IV: International Conference on Evolutionary Computation. the 4th International Conference on Parallel Pro

ISBN-13: 9783540617235 / Angielski / Miękka / 1996 / 1058 str.

Werner Ebeling; Ingo Rechenberg; Hans-Paul Schwefel

Opis

This book constitutes the refereed proceedings of the International Conference on Evolutionary Computation held jointly with the 4th Conference on Parallel Problem Solving from Nature, PPSN IV, in Berlin, Germany, in September 1996.
The 103 revised papers presented in the volume were carefully selected from more than 160 submissions. The papers are organized in sections on basic concepts of evolutionary computation (EC), theoretical foundations of EC, modifications and extensions of evolutionary algorithms, comparison of methods, other metaphors, and applications of EC in a variety of areas like ML, NNs, engineering, CS, OR, and biology. The book has a comprehensive subject index.

Spis treści

Computational brittleness and the evolution of computer viruses.- Evolutionary computing in multi-agent environments: Speciation and symbiogenesis.- Evolution strategies with subjective selection.- Emergent cooperation for multiple agents using genetic programming.- Evolution programs evolved.- Encoding scheme issues for open-ended artificial evolution.- Hardware evolution at function level.- Coevolutionary life-time learning.- Genetic programs and co-evolution.- Self-assemblage of gene nets in evolution via recruiting of new netters.- A survey of intron research in genetics.- Analytical and numerical investigations of evolutionary algorithms in continuous spaces.- On the asymptotic behavior of multirecombinant Evolution Strategies.- Are long path problems hard for genetic algorithms?.- Random tree generation for genetic programming.- Implicit formae in genetic algorithms.- A probabilistic database approach to the analysis of genetic algorithms.- Mean field analysis of tournament selection on a random manifold.- From recombination of genes to the estimation of distributions I. Binary parameters.- From recombination of genes to the estimation of distributions II. Continuous parameters.- Searching in the presence of noise.- The density of states — A measure of the difficulty of optimisation problems.- On interactive evolutionary algorithms and stochastic mealy automata.- The influence of different coding schemes on the computational complexity of genetic algorithms in function optimization.- An analysis of the effects of neighborhood size and shape on local selection algorithms.- Evolutionary computation at the edge of feasibility.- Dimensional analysis of allele-wise mixing revisited.- Gaussian diffusion in a simple genetic algorithm.- Erroneous truncation selection — A breeder's decision making perspective.- New crossover methods for sequencing problems.- The effect of extensive use of the mutation operator on generalization in genetic programming using sparse data sets.- On permutation representations for scheduling problems.- Multi-parent's niche: N-ary crossovers on NK-landscapes.- A preliminary investigation into directed mutations in evolutionary algorithms.- Heuristic crossovers for real-coded genetic algorithms based on fuzzy connectives.- Are evolutionary algorithms improved by large mutations?.- Mutation by imitation in boolean evolution strategies.- Formal algorithms + formal representations =search strategies.- A genetic algorithm with variable range of local search for tracking changing environments.- An Evolution Strategy with adaptation of the step sizes by a variance function.- Every niching method has its niche: Fitness sharing and implicit sharing compared.- Effects of isolation in a distributed population genetic algorithm.- Self-adaptive genetic algorithm for numeric functions.- Niche search: An evolutionary algorithm for global optimisation.- Adaptively parameterised evolutionary systems: Self adaptive recombination and mutation in a genetic algorithm.- Obtaining multiple distinct solutions with genetic algorithm niching methods.- Cost Based Operator Rate Adaptation: An investigation.- Genetic algorithms and relational landscapes.- IOGA: An instance-oriented genetic algorithm.- Explicit filtering of building blocks for genetic algorithms.- Multi-objective optimization by means of the thermodynamical genetic algorithm.- Adaptation to a changing environment by means of the thermodynamical genetic algorithm.- The development of a dual-agent strategy for efficient search across whole system engineering design hierarchies.- A parallel cellular genetic algorithm used in finite element simulation.- A robust solution searching scheme in genetic search.- Solving MasterMind using GAs and simulated annealing: A case of dynamic constraint optimization.- Evolving compact solutions in genetic programming: A case study.- Climbing up NP-hard hills.- On the performance assessment and comparison of stochastic multiobjective optimizers.- Paginating the generalized newspapers — A comparison of simulated annealing and a heuristic method.- A comparison of optimization techniques for integrated manufacturing planning and scheduling.- A comparison of search techniques on a wing-box optimisation problem.- A comparative study of evolutionary algorithms for on-line parameter tracking.- Modeling urban growth by cellular automata.- Democratic optimization for discrete and continuous systems.- A study of some properties of Ant-Q.- Immunoid: An immunological approach to decentralized behavior arbitration of autonomous mobile robots.- Parallelizable evolutionary dynamics principles for solving the maximum clique problem.- Significance of locality and selection pressure in the grand deluge evolutionary algorithm.- Parallel computing with DNA: Toward the anti-universal machine.- Tackling the “curse of dimensionality” of radial basis functional neural networks using a genetic algorithm.- A Three-stage method for designing Genetic Fuzzy Systems by learning from examples.- Learning heuristics for OBDD minimization by Evolutionary Algorithms.- Improving the generalization performance of multi-layer-perceptrons with population-based incremental learning.- Robust GP in robot learning.- A pattern recognition system using evolvable hardware.- Topology design of feedforward neural networks by genetic algorithms.- An evolution strategy for on-line optimisation of dynamic objective functions.- Exploiting competing subpopulations for automatic generation of test sequences for digital circuits.- Constraint handling in evolutionary search: A case study of the frequency assignment.- An application of genetic algorithms and neural networks to scheduling power generating systems.- Evolutionary algorithms for the calculation of electron distributions in Si-MOSFETs.- Refueling of a nuclear power plant: Comparison of a naive and a specialized mutation operator.- Genetic algorithms applied to the physical design of VLSI circuits: A survey.- Stochastic methods for transistor size optimization of CMOS VLSI circuits.- An adaptive parallel Genetic Algorithm for VLSI-layout optimization.- Genetic algorithms for protocol validation.- Constraint handling for the fault coverage code generation problem: An inductive evolutionary approach.- New genetic local search operators for the traveling salesman problem.- An evolutionary approach to hardware/software partitioning.- Evolutionary Air Traffic Flow Management for large 3D-problems.- Genetic-based dynamic load balancing: Implementation and evaluation.- Production scheduling with genetic algorithms and simulation.- Network optimization using evolutionary strategies.- Co-evolving parallel random number generators.- Scheduling by genetic local search with multi-step crossover.- Finding the conformation of organic molecules with genetic algorithms.- Investigating a Parallel Breeder Genetic Algorithm on the inverse Aerodynamic design.- An evolutionary design for f-? lenses.- Optimization of heat exchanger networks by means of evolution strategies.- Industrial plant pipe-route optimisation with genetic algorithms.- An evolutionary algorithm for design optimization of microsystems.- A learning classifier system for three-dimensional shape optimization.