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2020 | OriginalPaper | Chapter

22. A MATLAB-Based Application to Solve Vehicle Routing Problem Using GA

Authors : Nikki Rathore, P. K. Jain, M. Parida

Published in: Advances in Simulation, Product Design and Development

Publisher: Springer Singapore

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Abstract

Application of vehicle routing problem in real-life logistics operations is a need of today’s world, and this paper focuses on developing a vehicle routing problem for the delivery and pickup of products from multiple depot to the graphically scattered customers. The proposed model can be used in real-life applications of various logistic operations where there is a need to determine the optimized location of warehouse for setup so that the demand of customers is fully satisfied. To do so, a genetic algorithm-based solution methodology is proposed to solve the above-stated problem. The proposed algorithm is tested on generated data based on real-life scenarios. The experiments show that the proposed algorithm successfully finds the potential locations for warehouse setup based on the demand and location of customers for minimum transportation cost. The presented approach can provide good solutions to a large-scale problem generally found in real life.

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Literature
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go back to reference Alaia, E. Ben, Dridi, I.H., Bouchriha, H., Borne, P.: Insertion of new depot locations for the optimization of multi-vehicles multi-depots pickup and delivery problems using genetic algorithm. In: 2015 International Conference on Industrial Engineering and Systems Management (IESM), pp. 695–701. IEEE (2015) Alaia, E. Ben, Dridi, I.H., Bouchriha, H., Borne, P.: Insertion of new depot locations for the optimization of multi-vehicles multi-depots pickup and delivery problems using genetic algorithm. In: 2015 International Conference on Industrial Engineering and Systems Management (IESM), pp. 695–701. IEEE (2015)
7.
go back to reference Golden, B.L., Raghavan, S., Wasil, E.A.: The vehicle routing problem: latest advances and new challenges. Springer, Boston, MA, USA (2008)CrossRef Golden, B.L., Raghavan, S., Wasil, E.A.: The vehicle routing problem: latest advances and new challenges. Springer, Boston, MA, USA (2008)CrossRef
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go back to reference Özyurt, Z., Aksen, D.: Solving the multi-depot location-routing problem with lagrangian relaxation. In: Baker, E.K., Joseph, A., Mehrotra, A., Trick, M.A. (eds.) Extending the horizons: advances in computing, optimization, and decision technologies, pp. 125–144. Springer, Boston, MA, USA (2007)CrossRef Özyurt, Z., Aksen, D.: Solving the multi-depot location-routing problem with lagrangian relaxation. In: Baker, E.K., Joseph, A., Mehrotra, A., Trick, M.A. (eds.) Extending the horizons: advances in computing, optimization, and decision technologies, pp. 125–144. Springer, Boston, MA, USA (2007)CrossRef
17.
go back to reference Thangiah, S.R., Osman, I.H., Sun, T.: Hybrid genetic algorithm, simulated annealing and tabu search methods for vehicle routing problems with time windows. Comput. Sci. Dep. Slippery Rock Univ. Tech. Rep. SRU CpScTR9427. 1–37 (1993) Thangiah, S.R., Osman, I.H., Sun, T.: Hybrid genetic algorithm, simulated annealing and tabu search methods for vehicle routing problems with time windows. Comput. Sci. Dep. Slippery Rock Univ. Tech. Rep. SRU CpScTR9427. 1–37 (1993)
Metadata
Title
A MATLAB-Based Application to Solve Vehicle Routing Problem Using GA
Authors
Nikki Rathore
P. K. Jain
M. Parida
Copyright Year
2020
Publisher
Springer Singapore
DOI
https://doi.org/10.1007/978-981-32-9487-5_22

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