A Novel Assembly-Based Genetic Algorithm for Traveling Salesman Problem
Genetic algorithms and self-assembly computation appear to solve combinatorial optimization problems effiently. A novel assembly-based genetic algorithm for the traveling salesman problem is presented in the paper. To start with, some necessary notions and rules of assembly operator are introduced. Next, the flowchart of Assembly-Based Genetic Algorithm is given out. In addition, Traditional GA operators such as crossover and mutation are realized with assembly methods is proposed. Finally, we test the convergent rate of the algorithm and the best solution obtained by the algorithm after some generators. Experimental results show that the algorithm is feasible and effective
Congwen Zeng Tianlong Gu
School of Computer Science Guilin University of Electronic Technology Guilin 541004, China
国际会议
南宁
英文
2007-07-20（万方平台首次上网日期，不代表论文的发表时间）