An Efficient Algorithm for the Joint Replenishment Problem with Quantity Discounts, Minimum Order Quantity and Transport Capacity Constraints

The joint replenishment problem has been extensively studied and the strategy adopted by a large variety of retailers in recent years. However, under minimum order quantity other constraints does not receive sufficient attention. This paper analyzes retailing supply chain involving supplier that provides discount schedules limits quantity. include requirements for each item as to total quantity; additionally, latter cannot exceed transport capacity constraint. These are common retail industry today create greater complexity difficulty retailer’s decision-making. To analyze problem, an integer nonlinear programming model is set up maximize retailers’ profit with all practical constraints. A two-layer efficient algorithm named Marginal Cumulative Profit-Based Algorithm (MCPB) then proposed find whether optimal item. results computational experiments show can near-optimal solutions efficiently reference solve problems.