Paper Title:
Quantum Computing-Based Ant Colony Optimization Algorithm and Performance Analysis
| Periodical | Key Engineering Materials (Volumes 460 - 461) |
|---|---|
| Main Theme | Components, Packaging and Manufacturing Technology |
| Edited by | Yanwen Wu |
| Pages | 60-65 |
| DOI | 10.4028/www.scientific.net/KEM.460-461.60 |
| Citation | Xiao Ming You et al., 2011, Key Engineering Materials, 460-461, 60 |
| Online since | January, 2011 |
| Authors | Xiao Ming You, Sheng Liu, Xing Wai Miao |
| Keywords | Ant System, Multi Objective Optimization, Quantum Computing, Self-Adaptive Strategy |
| Price | US$ 28,- |
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Abstract
A novel Ant Colony Optimization algorithm based on Quantum mechanism for Multi-objective traveling salesman problem (MQACO) is proposed. To improve algorithm performance we use self-adaptive operator, namely in prophase we use higher probability to explore more search space and to collect useful global information; otherwise in anaphase we use higher probability to accelerate convergence. We analyze the technology to improve algorithm performance. Self-adaptive algorithm has advantages in terms of the adaptability; reliability and the learning ability over traditional organizing algorithm. TSP benchmark instances Chn144 results demonstrate the superiority of MQACO by different parameter in this paper.
