Using niching and sharing to find multiple solutions

In Chapter 2, Understanding the Key Components of Genetic Algorithms, we mentioned that niching and sharing in genetic algorithms mimic the way a natural environment is divided into multiple sub-environments, or niches. These niches are populated by different species, or sub-populations, taking advantage of the unique resources available in each niche, while specimens that coexist in the same niche have to compete over the same resources. Implementing a sharing mechanism within the genetic algorithm will encourage individuals to explore new niches and can be used for finding several optimal solutions, each considered a niche. One common way to accomplish sharing is to divide the raw fitness ...

Get Hands-On Genetic Algorithms with Python now with the O’Reilly learning platform.

O’Reilly members experience live online training, plus books, videos, and digital content from nearly 200 publishers.