Chambers L. (ed.) Practical Handbook of Genetic Algorithms. Complex Coding Systems. Volume 3

CRC Press, 1999. — 659 p.This is the third and probably last book in the Practical Handbook of Genetic AIgorithm series. The first volume dealt with applications, the second with new work in the field, and the present volume with computer code. I believe this set of three volumes completes main sections of the field that should be addressed, but I would be happy to be corrected on that score by anyone patient enough to let me know what other sectors should be covered.
Given the feedback I have received from readers of the two previous volumes, I am happy to present this third volume in the series to those who have an interest in the field. It presents computer code segments that can be downloaded from the CRC Press website and used by those undertaking research and/or are building real-world applications in the GA arena. It also contains detailed chapters covering the code and offering in-depth explanations and examples on the use of that code. A few chapters have been included because of their new/quirky uses of GAs; I believe readers will benefit from their content and perspectives. The remaining chapters contain material that is of more traditional value. They cover "problems" that are real and often encountered in the field.
I have not tested the code. You will need to do that either on your own or in collaboration with the author/s or others, if necessary. The main reason for development of this volume was the apparent paucity of material containing GA code in a single reference volume. There are a few books, papers, and articles that have code segments but not a single work that is dedicated to it. There was perceived to be a need for a reference that offered an array of code covering a number of applications. This book responds to that need and is designed to be of value to programmers who do not want to start from the beginning in developing solutions to particular problems but would rather have a work to which they can refer for code to start the process in a serious manner or where a particular problem solution or computation approach is sought.
The code presented by each author is available at the CRC Press website at: www.crcpress.com and is available for downloading at no cost. There is much to absorb and understand in this volume. If you have any particular queries on any of the material, contact details are given for each author on the first page of each contribution. Don't hesitate to get further help from the "horses mouth". Each of the authors would be happy to help; they are as proud of their contribution as I am to have edited them.
Hopefully, the chapters will also lead readers to new understandings and new ventures. There is still much work to be done in the application of GAs to the solution of problems that have, until now, been considered relatively intractable. The value that the GA fraternity has brought to academic, business, scientific, and social systems in the few years we have been in practice is something we should all view with pride. I do!
We are a young field with far to go and much to do and contribute. In less than three decades we have made a significant impact in many areas of human struggle and achievement and will continue to do so into the foreseeable future. It is my hope that this book will contribute to that progress.A Lamarckian Evolution Strategy for Genetic Algorithms
The Generalisation 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 Heuristic for Vehicle Routing Problems with Time Windows
Doing GAs with GAGS
Memory efficiency and speed enhancement code for GAs
Adaptive Portfolio Trading Strategies Using Genetic Algorithms
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
An Indexed Bibliography of Genetic Algorithm