Research On Combined Location Production Inventory Control Model And Algorithms Based On Demand Forecasting

Achieving logistics integration, improving logistics efficiency and reducing logistics costs are the hot issues in logistics and supply chain management. The combined location routing inventory control problem is the combination of LAP, VRP and LRP and other issues. CLRIP is the integration of logistics system as a whole from the perspective of a systematic vision of the logistics system optimization problem, which can optimize the logistics system. CLRIP is more in line with the actual characteristics of the complex logistics system.To achieve the optimization of supply chain system, ignoring the part of production is not really easy to realize. It’s to say that we should consider the combination of logistics integration and the integration of production, supply and distribution and analyse production and inventory control together, which is to consider the production, supply and distribution and inventory control, etc. based on logistics network design. In this paper we name this issue as the combined location production inventory control problem (CLPI). This paper commits to the research on CLPI, which is to achieve logistics integration and integration of production, supply and distribution in order to achieve the best of the system through rational design of the logistics network optimization, joint production-inventory control and sales logistics systems and transport path of the layout. The contents and methods of this paper are as follows:(1) Through the forecasting of the market demand of retailers, the gray forecast combined with time series decomposition model is builded to predict market demand for its high precision, and retailers make order strategies based on the results.(2) Through research and analysis of the manufacturer’s production, delivery and inventory, ordering and inventory control strategies for retailers, we build the joint production-inventory control model, which will really make the production issues to take account into the CLPI. (3) Based on (1) and (2), through the analysis and design of the selection and distribution schedule of RDC and the best regional transport routes of each RDC, we construct the total model of CLPI, which meet the actual characteristics of a complex logistics and supply chain system better than CLRIP.(4) The algorithms designed for the joint production-inventory model and CLPI model are also an important content of this paper. The algorithms designed in the paper play the role of guide and reference for solving problems in areas related to polynomials. Finally a numerical example is used to elaborate the CLPI issues.Based on demand forecasting, this paper systematically studies on the CLPI issues. It not only breaks through the bottleneck of previous studies, but also provides decision-making ideas and guidance for the actual problems of logistics and supply chain system.