Advertisement

Location Selection of Multiple Logistics Distribution Center Based on Particle Swarm Optimization

  • Qingyu ZengEmail author
  • Chengqi Li
  • Xiangbiao Wu
  • Shengjie Long
  • Zhuanzhou Zhang
  • Rui Liu
  • Tao Huang
  • Yanmin Liu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9771)

Abstract

Distribution center is an important pivot position at the logistics system. This paper presents the site selection’s model of logistics distribution center based on decision matrix C, which adopts particle swarm optimization (PSO) to find the best combination of site selection by structuring the iteration of decision matrix. At the same time, simulation experiments are conducting for the site selection of logistics distribution center with 4 candidate centers and 10 distribution points, and the results show that PSO can get the best solution of distribution center in 90 % success rate of the best solution and the average research time of the approximate 3.5 s. From simulation experiment, PSO is efficient, accurate and suitable for the model optimization of distribution center, and therefore, it can be regarded as an effective method for the site selection’s model of logistics distribution.

Keywords

Logistics Distribution center Particle swarm optimization 

Notes

Acknowledgments

This work is supported by the National Natural Science Foundation of China (Grants nos. 71461027, 71471158). Guizhou science and technology cooperation plan (Qian Ke He LH zi [2016]7028, Qian Ke He LH zi [2015]7050, [2015]7005, Qian Ke He J zi LKZS [2014]30). Science and technology talent training object of Guizhou province outstanding youth (Qian ke he ren zi [2015]06). Guizhou province natural science foundation in China (Qian Jiao He KY [2014]295); 2013, 2014 and 2015 Zunyi 15851 talents elite project funding; Zhunyi innovative talent team (Zunyi KH (2015) 38); Project of teaching quality and teaching reform of higher education in Guizhou Province (Qian Jiao gaofa [2013]446, [2015]337), College students’ innovative entrepreneurial training plan (201410664004, 201510664016).

References

  1. 1.
    Yuan, Y.X.: A scaled central path for linear programming. J. Comput. Math. 19(1), 35–40 (2001)MathSciNetzbMATHGoogle Scholar
  2. 2.
    Konstantinos, G.Z., Konstantinos, N.A.: A heuristic algorithm for solving hazardous materials distribution problems. Eur. J. Oper. Res. 152, 507–519 (2004)CrossRefzbMATHGoogle Scholar
  3. 3.
    Qian, J., Pang, X.H., Wu, Z.M.: An improved genetic algorithm for allocation optimization of distribution centers. J. Shanghai Jiaotong Uni. (Sci.) E9(4), 73–76 (2004)zbMATHGoogle Scholar
  4. 4.
    Dorigo, M., Gambardella, L.M.: Ant colony system: a cooperative learning approach to the traveling salesman problem. IEEE Trans. Evol. Comput. 1(1), 53–66 (1997)CrossRefGoogle Scholar
  5. 5.
    Gao, Z.H.: Application of particle swarm optimization to continuous location of distribution center. Comput. Appl. 28(9), 2401–2403 (2008)zbMATHGoogle Scholar
  6. 6.
    Wang, T.J., Wu, Y.C.: Study on optimization of logistics distribution route based on chaotic PSO. Comput. Eng. Appl. 47(29), 218–221 (2011)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Qingyu Zeng
    • 1
    Email author
  • Chengqi Li
    • 2
  • Xiangbiao Wu
    • 1
  • Shengjie Long
    • 1
  • Zhuanzhou Zhang
    • 1
  • Rui Liu
    • 1
  • Tao Huang
    • 1
  • Yanmin Liu
    • 1
  1. 1.School of Mathematics and ScienceZunyi Normal CollegeZunyiChina
  2. 2.School of Mathematics and ScienceWuyi UniversityJiangmenChina

Personalised recommendations