Shipping Products by two Product Distribution Methods and Comparing them by Considering Cross Docking

Document Type : Research/ Original/ Regular Article

Authors

1 Assistant Professor, Department of Industrial Engineering, AmirKabir University of Technology

2 Professor, Department of Industrial Engineering, AmirKabir University of Technology

3 M.S. Student of Industrial Engineering, AmirKabir University of Technology, Corresponding author

Abstract

 
The middle repository is a relatively new logistics technique that has been used successfully in a large number of retail chains. In this system, repositories instead of being points for storing goods, are coordinators of the stock. This paper by modeling two [1]objective functions simultaneously has simulated and optimized   the problem of routing vehicle with middle repository and possibility of slight sending of products to customers. In this way, vehicles after leaving repository through some routes collect goods from suppliers and return to repository and after the separation and integration of products within repository, distribute items among customers with respect to slight sending in routes or send items directly from factory to customers.
Because of the inherent complexity of integer hybrid models and their NP-hardness, they cannot be solved by exact methods. In this paper, optimization of the mass of particles and the Tabu search as two meta-heuristic algorithms and a heuristic algorithm for searching neighborhoods are used and the results of the five data sets with different sizes are analyzed. The findings show that the algorithm of optimization of the mass of particles despite being time-consuming finds acceptable and near-optimal solutions and heuristic algorithm of searching neighborhoods despite good results is in the second rank. However, in terms of time, it takes minimum time to find near-optimal solution.



 

Keywords

References

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History

  • Receive Date: 09 November 2016
  • Revise Date: 12 December 2017
  • Accept Date: 12 December 2017
  • Publish Date: 22 November 2017

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