Optimizing order picker problem using dynamic programming method

Document Type : Research Paper

Authors

1 Department of Mathematics, Faculty of Computer \& Mathematical Sciences, University Teknologi MARA, Cawangan Negeri Sembilan, Kampus Seremban, 70300 Seremban

2 Malaysia Institute of Transport (MITRANS), University Teknologi MARA, 40450 Shah Alam, Malaysia

3 Institute of Mathematical Sciences, University of Malaya, 50603 Kuala Lumpur, Malaysia

Abstract

The order picking problem is one of the key elements in warehouse management.  The challenge increases during the new norm when orders can be made by going to the shop and also via online that results in high uncertainty in order volume. Despite that, customer expectation remains on fast delivery which requires the selling organizations to be able to provide fast and efficient service to meet the demand from customers.  In achieving this, among the contributing factors is efficient warehouse management especially in order picking, storage assignment, sufficient resource allocation, adequate manpower handling and proper tasking allocation. Thus, in this paper, a model for order picking is modified by considering the limited picking capacity of the Order Pickers (OP), the S-shaped route in the warehouse plan and the need for complete order (all demanded items are picked). The modified model is adapted as a Dynamic Programming problem with the objective of minimizing the time taken (through minimizing distance travelled) in picking each order. The results show that testing with a set of secondary data, the modified model shows a reduction of 24.19\% in travel distance compared to using Shortest Path Problem (SPP) and Traveling Salesman Problem (TSP). At the same time, the application of the modified model using the real data shows a reduction of 11.6\% in the travelled distance as well as more quality task allocation among the OPs.

Keywords

[1] E. Ardjmand, H. Shakeri, M. Singh and O.S. Bajgiran, Minimizing order picking makespan with multiple pickers in a wave picking warehouse, Int. J. Product. Econ. 206 (2018) 169–183.
[2] B. Bahrami, E.H. Aghezzaf and V. Limere, Enhancing the order picking process through a new storage assignment strategy in forward-reserve area, Int. J. Product. Res. 57(21) (2019) 6593–6614.
[3] J.A. Cano, A. A. Correa-Espinal and R. A. Gomez-Montoya, An evaluation of picking routing policies to improve warehouse efficiency, Int. J. Indust. Engin. Manag. 8(4) (2017) 229–238.
[4] N. Christofides and J.E. Beasley, The period routing problem, Networks 14 (1984) 237–256.
[5] R. De Koster, T. Le Duc and K.J. Roodbergen, Design and control of warehouse order picking: A literature review, European J. Oper. Res. 182(2) (2007) 481–501.
[6] U.S.S. Dharmapriya and A.K. Kulatunga, New strategy for warehouse optimization-lean warehousing, Proc. 2011 Int. Conf. Indust. Engin. Oper. Manag. Kuala Lumpur, Malaysia, (2011) 513–519.
[7] A. Fumi, L. Scarabotti and M.M. Schiraldi, The effect of slot-code optimization in warehouse order picking, Int. J. Eng. Business Manag. 5 (2013) 5–20.
[8] Y. Gong and R. De Koster, A polling-based dynamic order picking system for online retailers, IIE Trans. 40 (2008) 1070–1082.
[9] P.A. Jensen and J.F. Bard, Operations Research Models and Methods, John Wiley and Sons Inc., 2003.
[10] A.N. Letchford, S.D. Nasiri and D.O. Theis, Compact formulations of the Steiner traveling salesman problem and related problems, European J. Oper. Res. 228 (2013) 83–92.
[11] N.A. Mohd Nordin, Real-Time Dispatching and Routing of The EMS Ambulances Using The Dijkstra-Based CTT Model: A Case Study of HTAR, MSc Thesis, Universiti Teknologi MARA, Malaysia, 2010.
[12] N.A. Mohd Nordin, M. Omar and S.S.R. Shariff, Comparison of Dijkstra’s algorithm and dynamic programming method in finding shortest path for order picker in a warehouse, 4th Int. Conf. Math. Sci. (ICMS4), Putrajaya, Malaysia, (2016).
[13] M. Napolitano, Warehouse/DC operations survey: mixed signal, Modern Mater. Handl. 51(11) (2012) 48–56.
[14] M.M. Nasiri, M. Aliakbarnia Omran and F. Jolai, Scheduling post-distribution cross-dock under demand uncertainty, Int. J. Nonlinear Anal. Appl. 10(Special Issue (Nonlinear Analysis in Engineering and Sciences)) (2019) 53–65.
[15] K.J. Roodbergen, Layout and Routing Methods For Warehouses, Ph.D. Thesis, Erasmus University Rotterdam, 2001.
[16] K.J. Roodbergen and R.D. Koster, Routing methods for warehouses with multiple cross aisles, Int. J. Product. Res. 39(9) (2001) 1865–1883.
[17] K.J. Roodbergen and R. De Koster, Routing order pickers in a warehouse with a middle aisle, European J. Oper. Res. 133(1) (2001) 32–43.
[18] S. Tabatabaei, M. Safi and M. Shafiei Nikabadi, A mathematical model for scheduling of transportation, routing, and cross-docking in the reverse logistics network of the green supply chain, Int. J. Nonlinear Anal. Appl. 12(2) (2021) 1909–1927.
[19] R.K. Tiwari, N.K. Khedlekar and U.K. Khedlekar, Optimal pricing policy for stock dependent demand with effective investment in preservation technology, Int. J. Nonlinear Anal. Appl. 12(2) (2021) 249–264.
[20] J.A. Tompkins, Facilities Planning, John Wiley & Sons, Inc., 2010.
Volume 13, Issue 1
March 2022
Pages 1985-1998
  • Receive Date: 03 October 2021
  • Revise Date: 13 November 2021
  • Accept Date: 21 November 2021