Dynamic setting of shipping points in logistics systems with multiple heterogeneous warehouses

• Authors: HERZOG Dobromir
• Languages of publication: EN

Abstracts

EN

This study aims to model a planning process of handling outbound deliveries from a set of geographically dispersed warehouses. The model incorporates parameters observed in real-life supply chains and allows simulation of various variants of process supporting decision making of current shipment management, as well as strategic planning of distribution network. A heuristic algorithm that can be used for planning source warehouses for shipments is proposed. The model is built and tested on real business data and its performance proves to be better than the one currently used by a reference company.

Keywords

EN

supply chain planning; distributed warehousing; internal logistics; warehousing policies

• Publisher: Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
• Journal: Operations Research and Decisions
• Year: 2021
• Volume: 31
• Issue: 2
• Pages: 93-108

Contributors

author

HERZOG Dobromir

• Wrocław University of Economics and Business, Logistics Department, Wrocław, Poland

References

• AGRAWAL V., CHAO X., SESHADRI S., Dynamic balancing of inventory in supply chains, Eur. J. Oper. Res., 2004, 159, 296–317.
• ANDERSON C., BOOMSMA J.J., BARTHOLDI J.J., Task partitioning in insect societies: bucket brigades, Ins. Soc., 2002, 49 (2), 171–180.
• AVCI M.G., SELIM H., A multi-objective simulation-based optimization approach for inventory replenishment problem with premium freights in convergent supply chains, Omega, 2018, 80, 153–165.
• BRATCU A.I., DOLGUI A., A survey of self-balancing production lines (“bucket brigade”), J. Int. Manuf., 2005, 16 (2), 139–158.
• BUSTILLO M., MENÉNDEZ B., PARDO E.G., DUARTE A., An algorithm for batching, sequencing and picking operations in a warehouse, Int. Conf. Industrial Engineering and Systems Management (IESM), IEEE, 2015, 842–849.
• DE KOSTER R., LE-DUC T., ROODBERGER K., Design and control of warehouse order picking. A literature review, Eur. J. Oper. Res., 2007, 182, 481–501.
• DIAZ R., Using dynamic demand information and zoning for the storage of non-uniform density stock keeping units, Int. J. Prod. Res., 2016, 54 (8), 2487–2498.
• DUAN Q., LIAO T.W., Optimization of replenishment policies for decentralized and centralized capacitated supply chains under various demands, Int. J. Prod. Econ., 2013, 142, 194–204.
• FRAZELLE E.H., APPLE J.M., Warehouse Operations in the Distribution Management Handbook, McGraw-Hill, New York 1994.
• GLOCK C.H., GROSSE E.H., Storage policies and order picking strategies in U-shaped order-picking systems with a movable base, Int. J. Prod. Res., 2012, 50 (16), 4344–4357.
• GUDEHUS T., KOTZAB H., Comprehensive logistics, Springer Science and Business Media, Berlin 2012, 579.
• HENN S., WÄSCHER G., Tabu search heuristics for the order batching problem in manual order picking systems, Eur. J. Oper. Res., 2012, 222 (3), 484–494.
• HSIEH L.F., HUANG Y.C., New batch construction heuristics to optimise the performance of order picking systems, Int. J. Prod. Econ., 2011, 131 (2), 618–630.
• JAKUBIAK M., TARCZYŃSKI G., Influence of zone picking, storage of goods, and warehouseman’s routing method on efficiency of order picking process, Optimum. Econ. Studies, 2017, 138–152 (in Polish).
• KŁODAWSKI M.,JACYNA M., Selected aspects of picking as a function of process labour intensity, Prace Naukowe Politechniki Warszawskiej, Warsaw 2009, 70, 73–84 (in Polish).
• KULAK O., SAHIN Y., TANER M.E., Joint order batching and picker routing in single and multiple-cross-aisle warehouses using cluster-based tabu search algorithms, Flex. Serv. Manuf. J., 2012, 24 (1), 52–80.
• LAU H.C., NAKANDALA D., A pragmatic stochastic decision model for supporting goods trans-shipments in a supply chain environment, Dec. Sup. Syst., 2012, 54 (1), 133–141.
• LI J., HUANG R., DAI J.B., Joint optimisation of order batching and picker routing in the online retailer’s warehouse in China, Int. J. Prod. Res., 2017, 55 (2), 447–461.
• LI J., MOGHADDAM M., NOF S.Y., Dynamic storage assignment with product affinity and ABC classification. A case study, Int. J. Adv. Manuf. Techn., 2016, 84 (9–12), 2179–2194.
• MANZINI R., ACCORSI R., GAMBERI M., PENAZZI S., Modeling class-based storage assignment over life cycle picking patterns, Int. J. Prod. Econ., 2015, 170, 790–800.
• MATULEWSKI M., KONECKA S., FAJFER P., WOJCIECHOWSKI A., Logistics systems, components, operations, examples, Logistyka, Poznań 2008 (in Polish).
• MOELLER K., Increasing warehouse order picking performance by sequence optimization, Soc. Behav. Sci., 2011, 20, 177–185.
• MUTINGI M., MBOHWA C., Optimizing order batching in order picking systems. Hybrid grouping genetic algorithm, Group. Gen. Alg., 2017, 666, 121–140.
• PAN J.C.H., SHIH P.H., WU M.H., Order batching in a pick-and-pass warehousing system with group genetic algorithm, Omega, 2015, 57, 238–248.
• PATERSON C., KIESMÜLLER G., TEUNTER R., GLAZEBROOK K., Inventory models with lateral transshipments. A review, Eur. J. Oper. Res., 2011, 210, 125–136.
• RATLIFF H.D., ROSENTHAL A.S., Order-picking in a rectangular Warehouse: A solvable case of the traveling salesman problem, Oper. Res., 1987, 31 (3), 515–533.
• SABO-ZIELONKA A., TARCZYŃSKI G., Comparison of order picking times for different warehouse routing methods on the example of a large logistics centre, Ekonometria 2014, 2 (44), 62–81 (in Polish).
• SCHMITT A.J., SUN S.A., SNYDER L.V., SHEN Z.J.M., Centralization versus decentralization: risk pooling, risk diversification, and supply chain disruptions, Omega, 2015, 52, 201–212.
• SCHOLZ A., SCHUBERT D., WÄSCHER G., Order picking with multiple pickers and due dates. Simultaneous solution of order batching, batch assignment and sequencing, and picker routing problems, Eur. J. Oper. Res., 2017, 263 (2), 461–478.
• SCHOLZ A., WÄSCHER G., Order batching and picker routing in manual order picking systems. The benefits of integrated routing, Central Eur. J. Oper. Res., 2017, 25 (2), 491–520.
• STANGER S.H., WILDING R., HARTMANN E., YATES N., COTTON S., Lateral transshipments: an institutional theory perspective, Int. J. Phys. Distr. Log. Manage., 2013, 43 (9), 747–767.
• TSAMIS N., GIANNIKAS V., MCFARLANE D.,LU W., STRACHAN J., Adaptive storage location assignment for warehouses using intelligent products, Studies Comp. Int., 2015, 594, 271–279.
• VAN WIJK A., ADAN I., VAN HOUTUM G., Optimal allocation policy for a multi-location inventory system with a quick response warehouse, Oper. Res. Lett., 2013, 41, 305–310.

Identifiers

DOI

10.37190/ord210204