Cloud feedback assistance based Hybrid evolution algorithm for optimal data solution

Abstract

This paper develops a cloud based parallel and distributed evolutionary hybrid algorithm with feedback assistance to help planners solve the data optimal problems such as travel salesman problems. Each step and type of evolution algorithm is established via various virtual machines in cloud. The proposed feedback assistance is based on the fitness evaluation result and survival ratio of evolution algorithm. The feedback assistance can interact with the evolution algorithm and emphasize the process with more survival individuals in the next generation of evolution algorithm. Taking the advantage of cloud and the proposed feedback assistance, system users can take less effort on deploying both computation power and storage space. The convergency of optimal solution can be enhanced. © 2013 Springer Science+Business Media Dordrecht.