Rolling planning method for two-stage logistics system under unsteady demand

Abstract

A rolling planning method for a two-stage logistics system under unsteady demand is proposed in this paper, which has two objectives. The first objective is to propose a mathematical model that estimates the optimal production quantities, delivery quantities, and inventory level to control stock-out and over-stock situations in a make-to-stock production system to minimize the total logistics cost. The second objective is to generate optimal routes to minimize the distances travelled while delivering products from centroids to stores when the truck capacity is limited. To achieve the second objective, a mathematical model is proposed for clustering stores which integrates the geographical locations of the stores, its unsteady demands, and the truck capacity. After clustering, the travelling salesman problem (TSP) technique is applied to generate the optimal route and travelled distances within the cluster. The proposed model and solution approach are implemented in an urban area in the numerical examples. The results show that the proposed model performs well in handling unsteady demands by minimizing the total logistics cost and controlling stock-out, and over-stock situations over the planning horizon.