The Crowding Approach to Niching in Genetic Algorithms

A wide range of niching techniques have been investigated in evolutionary and genetic algorithms. In this article, we focus on niching using crowding techniques in the context of what we call local tournament algorithms. In addition to deterministic and probabilistic crowding, the family of local tournament algorithms includes the Metropolis algorithm, simulated annealing, restricted tournament selection, and parallel recombinative simulated annealing. We describe an algorithmic and analytical framework which is applicable to a wide range of crowding algorithms. As an example of utilizing this framework, we present and analyze the probabilistic crowding niching algorithm. Like the closely related deterministic crowding approach, probabilistic crowding is fast, simple, and requires no parameters beyond those of classical genetic algorithms. In probabilistic crowding, sub-populations are maintained reliably, and we show that it is possible to analyze and predict how this maintenance tak...

• Type: Journal
• Year: 2008
• Where: EC
• Authors: Ole J. Mengshoel, David E. Goldberg
• Keywords: Algorithms, Deterministic Crowding, EC 2008, ECommerce, Probabilistic Crowding