Abstract
This paper analysis the basic principles of the genetic algorithm (GA) and simulated annealing algorithm (SA) thoroughly. According to the characteristics of mutil-objective location routing problem, the paper designs the hybrid genetic algorithm in various components, and simulate achieved the GSAA (Genetic Simulated Annealing Algorithm).Which architecture makes it possible to search the solution space easily and effectively without overpass computation. It avoids effectively the defects of premature convergence in traditional genetic algorithm, and enhances the algorithms global convergence. Also it improves the algorithms convergence rate to some extent by using the accelerating fitness function. Still, after comparing with GA and SA, the results show that the proposed Genetic Simulated Annealing Algorithm has better search ability. And the emulation experiments show that this method is valid and practicable.
Publisher
Trans Tech Publications, Ltd.
Reference8 articles.
1. Fuzzy Programming method for Distribution Center Location Problem in a Supply Chain [A]. Proceedings of 2010 International Conference on Management Science (ICMS 2010)[C]. (2010).
2. Boggs P T, Tolle J W. Sequential quadratic programming for large-scale nonlinear optimization. Journal of Computational and Applied Mathematics. (2000).
3. Study on Scheme Selection of Multistage Compounding Transportation [A]. Proceedings of International Conference on Engineering and Business Management (EBM2011)[C]. (2011).
4. Dicky Fatrias, Yoshiaki Shimizu. An Enhanced Two-phase Approach for Fuzzy Multi-objective Linear Programming in Supplier Selection Problem [A]. Proceedings of APIEMS 2011[C].
5. Hilsen Albie D. A Multi-Period Vehicle Routing Problem in A Reverse Logistics System with Recovery options [A]. Proceedings of APIEMS 2011[C]. (2011).
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献