Environmental adaption method for dynamic environment
Ashish Tripathi, Prateek Garbyal, K. K. Mishra, Arun Kumar Misra · 2014
An Environmental adaption Method (EAM) has been established earlier [2]. In this paper an Environmental Adaption Method for Dynamic Environment (EAMD) has been proposed, which has been specially designed with real valued parameters in dynamic environment. It simulates an environment which gradually becomes more deadly for its inhabitants and only the individuals who are able to adapt to this changing environment will survive and improve their fitness over time. This change in the environment causes the solutions to converge towards the optimal solutions. EAMD is compared with two cellular genetic algorithms (grid16, grid100), a single population genetic algorithm (ga100) and a hill climber on the Black Box Optimization test-bed at dimensions 2D and 10D on a set of 24 benchmark functions. The proposed algorithm gives better results than the existing algorithms.