摘要
近似算法在解决超大规模旅行商问题时无法获得高精度优化解(或者次优解),智能算法虽然可以获得精度高于近似算法的解,很难在合理时间内获得。采用改良的凸包近似算法构成初始解并结合大概率优化策略的遗传算法来解决超大规模旅行商问题,通过对rl11849(962313),brd14051(489721),和pla33810(70757880)等实例实验都在理想的时间内获得优化解。证明这种混合算法在解决超大规模TSP问题时具有优势。
The approximate algorithm can not obtain the high accuracy optimization solution(or sub optimal solution)when solving the problem of super large scale traveling salesman problem. Although the intelligent algorithm can obtain the solution of the algorithm with higher accuracy than the approximate algorithm,it is difficult to obtain the. By using the improved convex hull approximation algorithm and genetic algorithm are combined to constitute the initial solution of the probability optimization strategy to solve large scale traveling salesman problem,based on the rl11849(962313),brd14051(489721),and pla33810(70757880)and other examples of experiments in the ideal time to obtain optimal solution.It is proved that the hybrid algorithm has the advantage of solving the problem of super large scale TSP.
出处
《电子设计工程》
2017年第22期26-30,共5页
Electronic Design Engineering
关键词
智能算法
近似算法
超大旅行商问题
混合算法
intelligent algorithm
approximation algorithm
large traveling salesman problem
hybrid algorithm
作者简介
崔东（1992-）,男,辽宁沈阳人,硕士研究生.研究方向：规划识别.
