Towards a more complete classification system for dynamically changing environments
Julien Georges Omer Louis Duhain, Andries Petrus Engelbrecht · 2012
In spite of substantial research applying evolutionary algorithms and swarm based algorithms to solve dynamic problems, the classification of dynamic environments is missing universal standards. This paper examines the various methods used so far to characterise dynamic optimisation problems and proposes an inclusive classification system. Additionally, a way to generate environments of each type using the moving peak benchmark is described.