CAJ | 학술논문

提出了一种求解度约束最小生成树问题（DCMST）的模糊离散粒子群优化算法（PSO）,粒子编码采用Prüfer数编码机制,并引入模糊矩阵产生Prüfer数,迭代过程中加入归一化运算对位置矩阵进行修正,利用最大数法进行解模糊化。通过仿真实验验证了算法的有效性。
제출료일충구해도약속최소생성수문제（DCMST）적모호리산입자군우화산법（PSO）,입자편마채용Prüfer수편마궤제,병인입모호구진산생Prüfer수,질대과정중가입귀일화운산대위치구진진행수정,이용최대수법진행해모호화。통과방진실험험증료산법적유효성。
This paper puts forward a kind of degree-constrained minimum spanning tree problem of fuzzy discrete particle swarm optimization algorithm.In the new algorithm,particle encoding using Prüfer number coding mechanism,and the introduction of fuzzy matrices to generate Prüfer number,iterative process to join the normalized operation of position matrix correction,using the maximum number of defuzzification method.The simulation results show the effectiveness of the algorithm.