In recent years, the automotive industry has faced an unprecedented crisis. In particular, the zero-inventory approach, which has been widely pursued by many automobile companies, seems to be impractical in some real production contexts since it requires an inventory of all parts but in low amounts. In this paper, we investigate a new logistics method which collects automobile parts by integrating the progress-lane (P-LANE) into the corresponding vehicle routing problem. We propose a mixed integer programming formulation for this new model, which can simultaneously determines the trip routes to collect automobile parts, as well as the PLANE that each collected part should be assigned to, so as to minimize the total costs of the production and inbound logistics. The comparison with the zero-inventory model shows that the use of the PLANE within the milk-run system could significantly decrease the total costs and also improve the transportation efficiency. To be specific, for small and large size instances, the total costs of the zero-inventory model are about 10% and 30% higher than the ones with PLANE , respectively, which suggests that the periodic part collection model with PLANE could be more appropriate for automobile manufacturing.
This paper deals with the advanced planning and scheduling (APS) problem with multilevel structured products. A constraint programming model is constructed for the problem with the consideration of precedence constraints, capacity constraints, release time and due date. A new constraint programming (CP) method is proposed to minimize the total cost. This method is based on iterative solving via branch and bound. And, at each node, the constraint propagation technique is adapted for domain filtering and consistency check. Three branching strategies are compared to improve the search speed. The results of computational study show that the proposed CP method performs better than the traditional mixed integer programming (MIP) method. And the binary constraint heuristic branching strategy is more effective than the other two branching strategies. Hindawi Publishing Corporation
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