Metaheuristics for a new MINLP model with reduced response time for on-line order batching

Document Type : Article

Authors

1 Department of Industrial Engineering, South Tehran Branch, Islamic Azad University, Tehran, Iran

2 Department of Industrial Engineering, University of Tabriz, Tabriz, P.O. Box 51666-14766, Iran

3 Department of Mechanical Engineering, South Tehran Branch, Islamic Azad University, Tehran, Iran

Abstract

With increase in the inventory of stored items and in the number of orders received, the picking process and the response time gain greater importance. It should be noted that, in order to enhance the efficiency of warehouse management system, effective correlation and coordination between order batching and order picking process is of crucial role. In this paper, novel mixed integer nonlinear programming for on-line order batching is proposed for improving performance of the warehouse which in turn results in reducing the response time and idle times. The proposed method is based on a blocked warehouse using a zoning system, which is called Online Order Batching in Blocked Warehouse with One Picker for each Block (OOBBWOPB). The mentioned model is solved by using two algorithm of artificial bee colony (ABC) and Ant-colony (ACO). For proving the analyses and claims, two numerical examples as cases 1 and 2 are defined and analyzed by this algorithms in MATLAB environment. Based on the results, the proposed warehouse shows better performance with a substantial reduction in the average response time of a set of customer orders compare to zhang et al. (2017) results. It’s noteworthy that the ACO yields better results than ABC.

Keywords


  1. References

    1. Bartholdi, J. and S. Hackman, Warehouse & distribution science: Release 0.96. The Supply Chain and Logistics Institute, Georgia Institute of Technology. Atlanta, USA Google Scholar, 2014.
    2. Tompkins, J.A., et al., Facilities planning. 2010: John Wiley & Sons.
    3. Le-Duc, T. and R.M. de Koster, Travel time estimation and order batching in a 2-block warehouse. European Journal of Operational Research, 2007. 176(1): p. 374-388.
    4. Van Nieuwenhuyse, I. and R.B. de Koster, Evaluating order throughput time in 2-block warehouses with time window batching. International Journal of Production Economics, 2009. 121(2): p. 654-664.
    5. Melacini, M., S. Perotti, and A. Tumino, Development of a framework for pick-and-pass order picking system design. The International Journal of Advanced Manufacturing Technology, 2011. 53(9-12): p. 841-854.
    6. Pan, J.C.-H., P.-H. Shih, and M.-H. Wu, Order batching in a pick-and-pass warehousing system with group genetic algorithm. Omega, 2015. 57: p. 238-248.
    7. Van Nieuwenhuyse, I., R. de Koster, and J. Colpaert, Order batching in multi-server pick-and-sort warehouses. 2007.
    8. Henn, S. and V. Schmid, Metaheuristics for order batching and sequencing in manual order picking systems. Computers & Industrial Engineering, 2013. 66(2): p. 338-351.
    9. Pérez-Rodríguez, R., A. Hernández-Aguirre, and S. Jöns, A continuous estimation of distribution algorithm for the online order-batching problem. The International Journal of Advanced Manufacturing Technology, 2015. 79(1-4): p. 569-588.
    10. Yu, M. and R.B. De Koster, The impact of order batching and picking area zoning on order picking system performance. European Journal of Operational Research, 2009. 198(2): p. 480-490.
    11. Henn, S., Algorithms for on-line order batching in an order picking warehouse. Computers & Operations Research, 2012. 39(11): p. 2549-2563.
    12. Henn, S., Order batching and sequencing for the minimization of the total tardiness in picker-to-part warehouses. Flexible Services and Manufacturing Journal, 2015. 27(1): p. 86-114.
    13. Henn, S., S. Koch, and G. Wäscher, Order batching in order picking warehouses: a survey of solution approaches, in Warehousing in the global supply chain. 2012, Springer. p. 105-137.
    14. Zhang, J., et al., On-line order batching and sequencing problem with multiple pickers: A hybrid rule-based algorithm. Applied Mathematical Modelling, 2017. 45: p. 271-284.
    15. Nia, A.R., H. Haleh, and A. Saghaei, Energy-conscious dynamic sequencing method for dual command cycle unit-load multiple-rack automated storage and retrieval systems. Scientia Iranica. Transaction E, Industrial Engineering, 2017. 24(6): p. 3371-3393.
    16. Marandi, F. and S. Zegordi, Integrated production and distribution scheduling for perishable products. Scientia Iranica, 2017. 24(4): p. 2105-2118.
    17. Teimoury, E. and S. Kazemi, An integrated pricing and inventory model for deteriorating products in a two-stage supply chain under replacement and shortage. Scientia Iranica. Transaction E, Industrial Engineering, 2017. 24(1): p. 342.
    18. Chaharsooghi, S. and A. Sajedinejad, Determination of the number of kanbans and batch sizes in a JIT supply chain system. Scientia Iranica. Transaction E, Industrial Engineering, 2010. 17(2): p. 143.
    19. Gu, J., M. Goetschalckx, and L.F. McGinnis, Research on warehouse operation: A comprehensive review. European journal of operational research, 2007. 177(1): p. 1-21.
    20. Choe, K.-I., Aisle-based order pick systems with batching, zoning, and sorting. 1990, Georgia Institute of Technology.
    21. Tang, L.C. and E.-P. Chew, Order picking systems: batching and storage assignment strategies. Computers & Industrial Engineering, 1997. 33(3-4): p. 817-820.
    22. Elsayed, E., et al., Sequencing and batching procedures for minimizing earliness and tardiness penalty of order retrievals. The International Journal of Production Research, 1993. 31(3): p. 727-738.
    23. Henn, S., et al., Metaheuristics for the order batching problem in manual order picking systems. Business Research, 2010. 3(1): p. 82-105.
    24. Henn, S. and G. Wäscher, Tabu search heuristics for the order batching problem in manual order picking systems. European Journal of Operational Research, 2012. 222(3): p. 484-494.
    25. Hong, S., A.L. Johnson, and B.A. Peters, Large-scale order batching in parallel-aisle picking systems. IIE Transactions, 2012. 44(2): p. 88-106.
    26. Matusiak, M., et al., A fast simulated annealing method for batching precedence-constrained customer orders in a warehouse. European Journal of Operational Research, 2014. 236(3): p. 968-977.
    27. Valle, C.A., J.E. Beasley, and A.S. da Cunha, Optimally solving the joint order batching and picker routing problem. European Journal of Operational Research, 2017. 262(3): p. 817-834.
    28. Menéndez, B., et al., Variable neighborhood search strategies for the order batching problem. Computers & Operations Research, 2017. 78: p. 500-512.
    29. Menéndez, B., et al., General Variable Neighborhood Search for the Order Batching and Sequencing Problem. European Journal of Operational Research, 2017. 263(1): p. 82-93.
    30. Lin, C.-C., et al., Joint order batching and picker Manhattan routing problem. Computers & Industrial Engineering, 2016. 95: p. 164-174.
    31. Hong, S. and Y. Kim, A route-selecting order batching model with the S-shape routes in a parallel-aisle order picking system. European Journal of Operational Research, 2017. 257(1): p. 185-196.
    32. Scholz, A., D. Schubert, and G. Wäscher, Order picking with multiple pickers and due dates–Simultaneous solution of Order Batching, Batch Assignment and Sequencing, and Picker Routing Problems. European Journal of Operational Research, 2017. 263(2): p. 461-478.
    33. Muppani, V.R. and G.K. Adil, Efficient formation of storage classes for warehouse storage location assignment: a simulated annealing approach. Omega, 2008. 36(4): p. 609-618.
    34. Parikh, P.J. and R.D. Meller, Selecting between batch and zone order picking strategies in a distribution center. Transportation Research Part E: Logistics and Transportation Review, 2008. 44(5): p. 696-719.
    35. Chen, M.-C. and H.-P. Wu, An association-based clustering approach to order batching considering customer demand patterns. Omega, 2005. 33(4): p. 333-343.
    36. Gibson, D.R. and G.P. Sharp, Order batching procedures. European Journal of Operational Research, 1992. 58(1): p. 57-67.
    37. Gademann, N. and S. Velde, Order batching to minimize total travel time in a parallel-aisle warehouse. IIE transactions, 2005. 37(1): p. 63-75.
    38. Kulak, O., Y. Sahin, and M.E. Taner, Joint order batching and picker routing in single and multiple-cross-aisle warehouses using cluster-based tabu search algorithms. Flexible services and manufacturing journal, 2012. 24(1): p. 52-80.
    39. Cergibozan, Ç. and A.S. Tasan, Order batching operations: an overview of classification, solution techniques, and future research. Journal of Intelligent Manufacturing, 2016: p. 1-15.