Abstract
This study addresses warehouse storage location assignment problems (SLAP) where the traveling distance in an order-picking process is considered with three-axis traveling distance; two-horizontal and one-vertical distance. A mathematical model of the problem is first presented, then LINGO is used to find optimal solutions for a set of generated problems. However, as the problem size increases, computing time increases rapidly, and eventually the solution could not be found when the problem size is very large. Thus, this study presents an application of Differential Evolution (DE) algorithm to solve SLAP. The performance of proposed DE is evaluated on a set of generated problems, and the experimental results shows that the algorithm is able to provide good solutions especially for the large-size problems with relatively shorter computing time.
Access provided by Autonomous University of Puebla. Download to read the full chapter text
Chapter PDF
Similar content being viewed by others
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
References
Van Den Berg, J., Zijm, W.: Models for warehouse management: Classification and examples. Int. J. Prod. Econ. 59(1), 519–528 (1999)
Brynzer, H., Johansson, M.I.: Storage location assignment: using the product structure to reduce order picking times. Int. J. Oper. Res. 47, 595–603 (1996)
Heragu, S.S., Du, L., Mantel, R.J., Schuur, P.C.: Mathematical model for warehouse design and product allocation. Int. J. Pro. Res. 43(2), 327–338 (2005)
Chen, Y., He, F.: Research on particle swarm optimization in location assignment optimization. In: Proceedings of the 7th World Congress on Intelligent Control and Automation (2008)
Muppani, V.R., Adil, G.: Efficient formation of storage classes for warehouse storage location assignment: A simulated annealing approach. Int. J. Manag. Sci. 36, 609–618 (2008)
Muppani, V.R., Adil, G.K.: A branch and bound algorithm for class-based storage-location assignment. Eur. J. Oper. Res. 189, 492–507 (2008)
Hsu, C.M., Chen, K.Y., Chen, M.Y.: Batching orders in warehouse by minimizing travel distance with genetic algorithms. Comput. Ind. 56, 169–178 (2005)
Roodbergen, K.J., De Koster, R.: Routing methods for warehouses with multiple cross aisle. Int. J. Prod. Res. 39(9), 1865–1883 (2001)
Kasemset, C., Meesuk, P.: Storage location assignment considering three-axis traveling distance: A mathematical model. In: Golinska, P. (ed.) Logistics Operations, Supply Chain Management and Sustainability, EcoProduction, pp. 499–506. Springer, Heidelberg (2014)
Storn, R., Price, K.: Differential evolution – a simple and efficient adaptive scheme for global optimization over continuous spaces. Technical Report TR-95-012, International Computer Science, Berkeley, CA (1995)
Bierwirth, C.: A generalized permutation approach to job shop scheduling with genetic algorithms. In: Pesch, E., Vo, S. (eds.) OR-Spektrum. Special issue: Applied Local Search, vol. 17(213), pp. 87–92 (1995)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Wisittipanich, W., Meesuk, P. (2015). Differential Evolution Algorithm for Storage Location Assignment Problem. In: Gen, M., Kim, K., Huang, X., Hiroshi, Y. (eds) Industrial Engineering, Management Science and Applications 2015. Lecture Notes in Electrical Engineering, vol 349. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-47200-2_29
Download citation
DOI: https://doi.org/10.1007/978-3-662-47200-2_29
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-662-47199-9
Online ISBN: 978-3-662-47200-2
eBook Packages: Computer ScienceComputer Science (R0)