Modular Cloud Hybrid Evolution Algorithm Based on Feedback Assistance for Optimal Data Solution in Traveling Salesman Problem

• Main Authors: Kuan-wei Lee, 李寬瑋
• Other Authors: Ming-Shen Jian
• Format: Others
• Language: en_US
• Published: 2014
• Online Access: http://ndltd.ncl.edu.tw/handle/35h9tm

碩士 === 國立虎尾科技大學 === 資訊工程研究所 === 102 === This paper develops a modular cloud hybrid evolution algorithm based on feedback assistance for optimal data solution in traveling salesman problem. Different steps and types of the evolution algorithm can be established via individual thread procedures and various virtual machines in cloud. According to the proposed XML format, system users can upload only the coding of chromosomes without the evolution algorithm implementation. The proposed feedback assistance is based on the fitness evaluation result and survival ratio of different crossover methods. The Reduce the cost for establishing the evolution algorithm according to the proposed system can. The feedback assistance can interact with the different crossover methods and emphasize the method that can enhance more survival individuals for the next evolution generation. Furthermore, via using the feedback assistance, the convergence time of the optimal solution can be enhanced.