| 基于Prüfer数的离散粒子群优化算法在TSP问题中的应用 |
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| 引用本文： | 严坤妹.基于Prüfer数的离散粒子群优化算法在TSP问题中的应用[J].福州大学学报(自然科学版),2017,45(1):147-150. |
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| 作者姓名： | 严坤妹 |
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| 作者单位： | 福建商业高等专科学校 |
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| 摘 要： | 通过引入Prüfer数编码、归一化运算、粒子的位置矩阵进行模糊化等操作,将连续型粒子群优化算法改造为离散化PSO.并通过构造旅行商问题的度约束最小生成树,利用DCMST的模糊离散粒子群算法求出最优解.采用TSP的测试实例进行仿真实验,证明算法的有效性与实用性.
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| 关 键 词： | Prüfer数编码 粒子群优化算法 度约束最小生成树 TSP 问题 |
A Discrete Particle Swarm Optimization Algorithm Based on Prufer Number for the Application of the TSP Problem |
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| YAN Kunmei.A Discrete Particle Swarm Optimization Algorithm Based on Prufer Number for the Application of the TSP Problem[J].Journal of Fuzhou University(Natural Science Edition),2017,45(1):147-150. |
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| Authors: | YAN Kunmei |
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| Institution: | Fujian Commercial College |
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| Abstract: | Particle swarm optimization (PSO) is now becoming a hotspot in the research of the artificial intelligence subject. The Prüfer number coding mechanism, the normalized operation, and the fuzzification of the particle"s position matrix are designed for transform the continuous PSO into discrete PSO in this paper. Then the fuzzy discrete particle swarm optimization algorithm of degree-constrained minimum spanning tree (DCMST) is designed to solve the travelling salesman problem (TSP) problem. The benchmark for TSP is simulated and the simulation results show the effectiveness of the algorithm. |
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