An Effective Particle Swarm Optimization Algorithm Embedded in SA to solve the Traveling Salesman Problem
The heuristic methods have been widely developed for solution of complicated optimization methods. Recently hybrid methods that are based on combination of different approaches have shown more potential in this regard. This paper also introduces a new method by embedding the idea of particle swarm (PS) intelligence into the well-known method of simulated annealing (SA). This way SA has been capable to search a subspace of the search space by means of an individual particle; therefore the annealing process can start from lower temperatures and use shorter Markov chains for each particle, leading to faster solutions. The results obtained with the proposed method show its potential in achieving both accuracy and speed in small and medium size problems, compared to many advanced methods.
Traveling Salesman Problem Simulated Annealing Particle Swarm Optimization Combinatorial Optimization
H. Shakouri G. K. Shojaee H. Zahedi
H. Shakouri G. is with Dep. of Industrial Engineering, University of Tehran, Tehran, Iran. K. Shojaee is with IC Design Laboratory, Dept. of Electrical and Computer Engineering, University of Hadi Zahedi is a PhD student at Dep. of Computer Engineering, Ferdowsi University of Mashhad.
国际会议
2009年中国控制与决策会议(2009 Chinese Control and Decision Conference)
广西桂林
英文
5545-5550
2009-06-17（万方平台首次上网日期，不代表论文的发表时间）