Parallel Quantum Ant Colony Optimization Algorithm
The concept of the ant colony optimization technique for finding approximate solutions to traveling salesman problem is described. A novel Parallel Quantum Ant Colony Optimization Algorithm (QPACO) is proposed. The use of improved 3-opt mechanism and adaptive quantum interaction provides this methodology with superior local search ability; several antibody diversification schemes were incorporated into the QPACO in order to improve the balance between exploitation and exploration. Parallel implementations aim to provide further diversity by using multi-populations and inter-population migration strategies. It can maintain quite nicely the population diversity and help to obtain the optimal solutions rapidly. We describe the quantum parallel mechanism and analysis the technology of improving performance,the efficiency of the approach has been illustrated by applying to TSP benchmark instances Chn144.
Quantum Computing Parallel Mechanism Quantum Ant Colony Optimization Algorithm Self-adaptive Strategy
Xiaoming You
College of Electronic and Electrical Engineering,Shanghai University of Engineering Science, Shanghai, China
国际会议
上海
英文
346-347
2010-12-10（万方平台首次上网日期，不代表论文的发表时间）