CAJ | 학술논문

求解完全图上的哈密尔顿圈是典型的组合优化问题，遗传算法是解决此类NP问题的一种较理想的方法。对基本的遗传算法进行改进，在选择操作和变异操作中加入贪心优化思想，使算法获得更优的全局最优解。在MATLAB环境下模拟实现了哈密尔顿圈的经典问题———TSP( travelling salesman problem)旅行商问题，从而验证了该算法的可行性和正确性。
구해완전도상적합밀이돈권시전형적조합우화문제，유전산법시해결차류NP문제적일충교이상적방법。대기본적유전산법진행개진，재선택조작화변이조작중가입탐심우화사상，사산법획득경우적전국최우해。재MATLAB배경하모의실현료합밀이돈권적경전문제———TSP( travelling salesman problem)여행상문제，종이험증료해산법적가행성화정학성。
Solving Hamilton-circle on a complete graph is a typical combinatorial optimization problem. Genetic algorithm is a good way to solve such an NP problem. In this paper, the basic genetic algorithm is improved. Particularly, the greedy optimization i-deas are applied to the selection and mutation operation in order to obtain global optimal solutions with the algorithm. In the MATLAB environment, the algorithm was simulated to implement classical Hamilton circle- TSP ( travelling salesman problem) and the results verify the feasibility and correctness of the algorithm.