6 Evolutionary Programming and Heuristic Optimization
6.1 Introduction
The evolutionary computational techniques initiated by Fraser, Bremermann, and Reed in the 1950s [1] and developed by Lawrence Fogel [2] are bio-inspired methodologies that address combinatorial optimization problems. There are a host of techniques in this category, which include particle swarm, ant colony, genetic algorithms (GAs), and artificial intelligence, which learn or adapt to new situations, generalize, abstract, discover, and associate.
Evolutionary algorithms use a population of individuals, where an individual is referred to as a chromosome, which defines the characteristics of individuals in the population. The characteristic of each individual is termed ...
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