| 基于改进粒子群优化算法求解旅行商问题 |
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| 引用本文： | 王翠茹,冯海迅,张江维,袁和金. 基于改进粒子群优化算法求解旅行商问题[J]. 微计算机信息, 2006, 22(22): 273-275 |
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| 作者姓名： | 王翠茹 冯海迅 张江维 袁和金 |
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| 作者单位： | 071003,保定,华北电力大学计算机科学与技术学院 |
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| 摘 要： | 本文提出了一种改进粒子群优化算法:在算法中引入了速度变异机制和粒子自探索机制。这种改进后的学习行为更符合自然界生物的学习规律,更有利于粒子发现问题的全局最优解。用改进后的粒子群算法求解标准的旅行商问题,数字仿真表明了算法有效性。
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| 关 键 词： | 粒子群算法 改进粒子群算法 旅行商问题 |
| 文章编号： | 1008-0570(2006)08-1-0273-03 |
| 修稿时间： | 2005-12-09 |
Solving Traveling Salesman Problem Based on Improved Particle Swarm Optimization Algorithm |
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| Wang,Cuiru,Feng,Haixun,Zhang,Jiangwei,Yuan,Hejin. Solving Traveling Salesman Problem Based on Improved Particle Swarm Optimization Algorithm[J]. Control & Automation, 2006, 22(22): 273-275 |
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| Authors: | Wang Cuiru Feng Haixun Zhang Jiangwei Yuan Hejin |
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| Abstract: | An improved particle swarm optimization algorithm is proposed, the mutation of velocity and the tentative behavior of parti-cles have been introduced according to the phenomena of nature. In this way, the behavior of particles accords with the biological natural law even more, and easily find the global optimum solution. For solving benchmark traveling salesman problem, numerical simulation results shows the effectiveness and efficiency of the proposed method. |
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| Keywords: | Particle Swarm Optimization Algorithm IPSO Traveling Salesman Problem |
| 本文献已被 CNKI 万方数据 等数据库收录！ |
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