Practical Handbook of Genetic Algorithms Complex Coding Systems, Volume III
Coordonnateur : Chambers Lance D.
Practical Handbook of Genetic Algorithms, Volume 3: Complex Coding Systems contains computer-code examples for the development of genetic algorithm systems - compiling them from an array of practitioners in the field.
Each contribution of this singular resource includes:
Practical Handbook of Genetic Algorithms, Volume 3: Complex Coding Systems complements the first two volumes in the series by offering examples of computer code. The first two volumes dealt with new research and an overview of the types of applications that could be taken with GAs. This volume differs from its predecessors by specifically concentrating on specific functions in genetic algorithms, serving as the only compilation of useful and usable computer code in the field.
A Lamarckian Evolution Strategy for Genetic Algorithms. The Generalization and Solving of Timetable Scheduling Problems. Implementing Fast and Flexible Parallel Genetic Algorithms. Pattern Evolver. Matrix-Based GA Representations in a Model of Evolving Animal Communication. Algorithms to Improve the Convergence of a Genetic Algorithm with a Finite State Machine Genome. A Synthesizable VHDL Coding of a Genetic Algorithm. Genetic Algorithm Model Fitting. A Hybrid Genetic Algorithm, Simulated Annealing and Tabu Search Heuristics for Vehicle Routing Problems with Time Windows. Doing Gas with GAGS. Memory Efficiency and Speed Enhancement Code for Gas. Adaptive Portfolio Trading Strategies. Population Size, Building Blocks, Fitness Landscape and Genetic Algorithm Search Efficiency in Combinatorial Optimization: An Empirical Study. Experimental Results on the Effects of Multi-Parent Recombination: An Overview. Appendix.
NTI/Sales Copy
Date de parution : 12-2020
15.6x23.4 cm
Thèmes de Practical Handbook of Genetic Algorithms :
Mots-clés :
VHDL Code; GAs; fitness; Fit Mathematical Models; function; GA Process; complex; Vice Versa; coding; Fitness Function; systems; Fitness Landscape; tournament; Np Complete Problem; selection; Simple Genetic Algorithm; operator; Fitness Evaluation Function; evaluation; Parallel GAs; landscape; GA Parameter; chromosome structure; GA Search; complex coding systems; Unsigned Int; multi-parent recombination; Unsigned Integer; Lamarckian evolution; TS; genetic algorithm; SA; Gray Patterns; Timetabling Problems; Variable Length Chromosomes; Trading Model; Time Complexity Function; Genetic Sectoring; Genetic Operators