Despite their practical importance, not much theoretical research has been done on Lateral Shipment policies (LSPs). LSP methods are extensively used in the Supply Chain Industry to reduce product stock outs. Essentially a Lateral Shipment involves redistributing stock among retailers instead of making emergency orders to the warehouse. The use of efficient LSPs can reduce the cost of emergency replenishments and also prevent stock outs that lead to loss of sales and customer dissatisfaction.
One interesting paper about LSPs is that of Banerjjee et al. (2003) where the authors use discrete event simulation to study two LSPs which they call TBA and TIE. The comparison is being done under the assumption of an unlimited capacity warehouse and under various conditions like different number of retailers in the system, different levels of expected demand variability among the retailers as well as different levels of demand uncertainty.
Extending the work of Banerjee et al. (2003) I introduced and suggested a new Hybrid policy and also expanded the system to a three echelon system. This involved implementing a replenishment policy for the warehouse as well as two different Rationing Policies (policies of distributing a limited stock to retailers).
The first part of my experimentation was to reproduce Banerjee et al. (2003) experiment and to compare the results with my suggested policy. The second part involved studying of all LSPs under limited supply.
Implementing the simulation models with Enterprise Dynamics (ED) was an easy choice since the tool offers the simplicity of working in a graphical environment without any sacrifice in flexibility and power. I saved a lot of time in modelling, taking advantage of the existing functionalities of the ED atoms. I was also surprised by the power of the 4DScript programming language which allowed me to develop all three heuristics (LSPs) for my models.
Finally, the set up and the results analysis of my extensive experimentation, which involved 21 models, was made much easier by the combination of the Scenario Manager and the Excel ActiveX connections that are part of ED.
The results show that the suggested Hybrid policy over performs the other two, as it manages to reduce the Average Units of stock out per retailer as well as the Average Days Units of Stock (back-ordered units multiplied by the days the remain in stock out). These improved results can especially be seen for larger numbers of retailers. This is because of the larger pool of available inventories that can be redistributed.
Useful conclusions could also be made about the effect of limited supply on the LSPs. The results made clear that small changes in the average supply of the retailers deteriorate all performance measures significantly and also significantly increased the volatility of the results. However still under those conditions the Hybrid policy performed better than the TBA policy and comparable to TIE. Many other interesting extensions are also possible with the developed models. For example, the implementation of different replenishment policies for the warehouse, the clustering of retailers according to distance or the optimization of the redistribution route etc.
Ioannis Goniadis MSc in Operations Research University of Amsterdam.
A. Banerjee, J. Burton, and S. Banerjee. A simulation study of lateral shipments in single supplier, multiple buyers supply chain networks. International Journal of Production Economics 81: 103–114, 2003.
One interesting paper about LSPs is that of Banerjjee et al. (2003) where the authors use discrete event simulation to study two LSPs which they call TBA and TIE. The comparison is being done under the assumption of an unlimited capacity warehouse and under various conditions like different number of retailers in the system, different levels of expected demand variability among the retailers as well as different levels of demand uncertainty.
Extending the work of Banerjee et al. (2003) I introduced and suggested a new Hybrid policy and also expanded the system to a three echelon system. This involved implementing a replenishment policy for the warehouse as well as two different Rationing Policies (policies of distributing a limited stock to retailers).
The first part of my experimentation was to reproduce Banerjee et al. (2003) experiment and to compare the results with my suggested policy. The second part involved studying of all LSPs under limited supply.
Implementing the simulation models with Enterprise Dynamics (ED) was an easy choice since the tool offers the simplicity of working in a graphical environment without any sacrifice in flexibility and power. I saved a lot of time in modelling, taking advantage of the existing functionalities of the ED atoms. I was also surprised by the power of the 4DScript programming language which allowed me to develop all three heuristics (LSPs) for my models.
Finally, the set up and the results analysis of my extensive experimentation, which involved 21 models, was made much easier by the combination of the Scenario Manager and the Excel ActiveX connections that are part of ED.
The results show that the suggested Hybrid policy over performs the other two, as it manages to reduce the Average Units of stock out per retailer as well as the Average Days Units of Stock (back-ordered units multiplied by the days the remain in stock out). These improved results can especially be seen for larger numbers of retailers. This is because of the larger pool of available inventories that can be redistributed.
Useful conclusions could also be made about the effect of limited supply on the LSPs. The results made clear that small changes in the average supply of the retailers deteriorate all performance measures significantly and also significantly increased the volatility of the results. However still under those conditions the Hybrid policy performed better than the TBA policy and comparable to TIE. Many other interesting extensions are also possible with the developed models. For example, the implementation of different replenishment policies for the warehouse, the clustering of retailers according to distance or the optimization of the redistribution route etc.
Ioannis Goniadis MSc in Operations Research University of Amsterdam.
A. Banerjee, J. Burton, and S. Banerjee. A simulation study of lateral shipments in single supplier, multiple buyers supply chain networks. International Journal of Production Economics 81: 103–114, 2003.
