Quantum Dynamic Mechanism-based Parallel Ant Colony Optimization Algorithm

被引：0
|
作者：
You, Xiao-ming [1 ]
Liu, Sheng [2 ]
Wang, Yu-ming [2 ]
机构：
[1] Shanghai Univ Engn Sci, Coll Elect & Elect Engn, Shanghai 200065, Peoples R China
[2] Shanghai Univ Engn Sci, Sch Management, Shanghai 200065, Peoples R China
来源：
INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE SYSTEMS | 2010年 / 3卷
基金：
上海市自然科学基金; 中国国家自然科学基金;
关键词：
Quantum Dynamic Mechanism; Ant system; Self-adaptive strategy; Parallelization; TSP optimization;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
A novel Parallel Ant Colony Optimization Algorithm based on Quantum dynamic mechanism for traveling salesman problem (PQACO) is proposed. The use of the improved 3-opt operator provides this methodology with superior local search ability; several antibody diversification schemes were incorporated into the PQACO in order to improve the balance between exploitation and exploration. We describe the quantum dynamic mechanism and analysis the technology of improving performance, the efficiency of the approach has been illustrated by applying to TSP benchmark instances Chn144.
引用
收藏
页码：101 / 113
页数：13
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