Determining Batch Size In A Supply Chain

In a supply chain environment, determining batch size at each stage is of importance. Using large batch size can save costs but time is wasted as trade-off. Small batch size can speed up the process but costs are increasing. To represent both aspects, this paper proposes the nonlinear integer mathematical model with the objective function of minimizing both costs and time simultaneously. This model can be used to determine (production) batch size to match up the flow of production at manufacturer with the demand at retailers and means of shipment (transfer batch size). Since the nature of this problem is NP-hard, at each stage of supply chain, the acceptable production and transfer batch sizes are obtained using the advantage of genetic algorithm approach. The numerical illustration and results show that it is not necessary to use the same batch size when manufacturing and transferring.