Cloud Based Software Computing as a Service in Hybrid Evolution Algorithm with Feedback Assistance

Abstract

This paper develops cloud based software computing as a service (SCaaS) in the hybrid evolution algorithm with feedback assistance to solve the data optimal NP-complete problems such as travel salesman problems and job shop scheduling problems. Suitable steps, methods, or procedures of the genetic algorithm can be adopted from various evolution procedures or methods of the genetic algorithms based on the fitness evaluation results and survival ratio of different crossover methods in the current generation. The proposed system can dynamically emphasize the corresponding methods or procedures for the better performance in optimal solution searching. In addition, according to the proposed XML format, system users can upload only the coding of chromosomes without implementing the genetic algorithm program. Furthermore, by using the feedback assistance, the convergence time of the optimal solution can be enhanced.