Paper Title:
Quantum Computing-Based Ant Colony Optimization Algorithm and Performance Analysis
  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.

  Info
Periodical
Key Engineering Materials (Volumes 460-461)
Edited by
Yanwen Wu
Pages
60-65
DOI
10.4028/www.scientific.net/KEM.460-461.60
Citation
X. M. You, S. Liu, X. W. Miao, "Quantum Computing-Based Ant Colony Optimization Algorithm and Performance Analysis", Key Engineering Materials, Vols. 460-461, pp. 60-65, 2011
Online since
January 2011
Export
Price
$32.00
Share

In order to see related information, you need to Login.

In order to see related information, you need to Login.

Authors: Pin Yang Rao
Chapter 4: NEMS/MEMS Technology and Equipment
Abstract:The torsion bar is one of the major parts of converter tilting mechanism and is widely used for light weight, large energy stored in unit...
295
Authors: Si Lian Xie, Tie Bin Wu, Shui Ping Wu, Yun Lian Liu
Chapter 18: Computer Applications in Industry and Engineering
Abstract:Evolutionary algorithms are amongst the best known methods of solving difficult constrained optimization problems, for which traditional...
2846
Authors: Bei Zhan Wang, Xiang Deng, Wei Chuan Ye, Hai Fang Wei
Chapter 13: Mechanical Control and Information Processing Technology
Abstract:The particle swarm optimization (PSO) algorithm is a new type global searching method, which mostly focus on the continuous variables and...
1787
Authors: Jian Xue Chen, Shui Yu
Chapter 4: Mechatronics and Automation Manufacturing Systems, Control Technologies
Abstract:Combining ant colony optimization (ACO) algorithm with back-propagation (BP) algorithm, the ACO-BP algorithm is proposed to optimize shift...
553
Authors: Hai Yan Wang
Chapter 6: Production Management
Abstract:This paper presents a hybrid algorithm to address the flexible job-shop scheduling problem (FJSP). Based on Differential Evolution (DE), a...
502