8 Genetic algorithm variants
This chapter covers
- Introducing the Gray-coded genetic algorithm
- Understanding real-valued GA and its genetic operators
- Understanding permutation-based GA and its genetic operators
- Understanding multi-objective optimization
- Adapting genetic algorithms to strike a balance between exploration and exploitation
- Solving continuous and discrete problems using GA
This chapter continues with the topic of chapter 7: we will look at various forms of genetic algorithms (GAs) and delve deeper into their real-world applications. We’ll also look at a number of case studies and exercises, such as the traveling salesman problem (TSP), proportional integral derivative (PID) controller design, political districting, the cargo bike ...
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