1. Introduction. - 1. 1 What is Genetic Programming?. - 1. 2 Motivation. - 1. 3 Outline. - 2. Survey. - 2. 1 Introduction. - 2. 2 Genetic Algorithms. - 2. 3 Genetic Programming. - 2. 4 GP Research. - 2. 5 GP Applications. - 2. 6 Conclusions. - 3. Advanced Genetic Programming Techniques. - 3. 1 Background. - 3. 2 Tournament Selection. - 3. 3 Steady State Populations. - 3. 4 Indexed memory. - 3. 5 Scalar Memory. - 3. 6 Multi-tree programs. - 3. 7 Directed Crossover. - 3. 8 Demes. - 3. 9 Pareto Optimality. - 3. 10 Conclusions. - 4. Evolving a Stack. - 4. 1 Problem Statement. - 4. 2 Architecture. - 4. 3 Choice of Primitives. - 4. 4 Fitness Function. - 4. 5 Parameters. - 4. 6 Results. - 4. 7 Summary. - 5. Evolving a Queue. - 5. 1 Problem Statement. - 5. 2 Architecture. - 5. 3 Choice of Primitives. - 5. 4 Fitness Functions. - 5. 5 Parameters. - 5. 6 Automatically Defined Functions. - 5. 7 Evolved Solutions Caterpillar. - 5. 8 Evolved Programs Shuffler. - 5. 9 Circular Buffer Given Modulus Increment. - 5. 10 Circular Buffer Evolving Modulus Increment. - 5. 11 Discussion: Building Blocks and Introns. - 5. 12 Summary. - 6. Evolving a List. - 6. 1 Problem Statement. - 6. 2 Architecture. - 6. 3 Automatically Defined Functions. - 6. 4 Choice of Primitives. - 6. 5 Fitness Function. - 6. 6 Directed Crossover. - 6. 7 Parameters. - 6. 8 Results. - 6. 9 Software Maintenance. - 6. 10 Discussion. - 6. 11 Conclusions. - 7. Problems Solved Using Data Structures. - 7. 1 Balanced Bracket Problem. - 7. 2 Dyck Language. - 7. 3 Evaluating Reverse Polish Expressions. - 7. 4 Work by Others on Solving Problems with Memory. - 7. 5 Summary. - 8. Evolution of GP Populations. - 8. 1 Price's Selection and Covariance Theorem. - 8. 2 Fisher's Fundamental Theorem of Natural Selection. - 8. 3 Evolution of Stack Problem Populations. - 8. 4 Loss of Variety. - 8. 5 Measurements of GP Crossover's Effects. - 8. 6Discussion. - 8. 7 Summary. - 9. Conclusions. - 9. 1 Recommendations. - 9. 2 Future work. - References. - Appendices. - ANumber of Fitness Evaluations Required. - BGlossary. - CScheduling Planned Maintenance of the National Grid. - C. 1 Introduction. - C. 2 The Electricity Transmission Network in Great Britain. - C. 3 The South Wales Region of the UK Electricity Network. - C. 4 Approximating Replacement Generation Costs. - C. 5 The Fitness Function. - C. 6 The Chromosome. - C. 7 Greedy Optimisers. - C. 8 South Wales Problem without Contingencies. - C. 9 South Wales and Genetic Programming. - C. 10 South Wales Problem with Contingencies. - C. 11 Conclusions. - C. 12 Future Work. - C. 13 Using QGAME. - DImplementation. - D. 1 GP-QUICK. - D. 2 Coding Changes to GP-QUICK-2. 1. - D. 3 Default Parameters. - D. 4 Network Running. - D. 5 Reusing Ancestors Fitness Information. - D. 6 Caches. - D. 7 Compressing the Check Point File. - D. 8 Benchmarks. - D. 9 Code. Language: English