Research On The Optimization Model For Production Planning Under The Dynamic Electricity Price Environment

Manufacturing industry is under pressure to control costs, energy costs accounted for a huge proportion, especially the cost of electricity. How to control energy costs to enhance the competitiveness of enterprises is of great significance.Because electricity is the product of energy conversion, the rising of energy prices will indirectly lead to the rising of electricity price. In this paper, taken the power resources as the object, we study the task of optimizing the production tasks of enterprises under the dynamic electricity price environment. This has practical significance for enterprises to reduce energy costs. Past production research did not take into account energy prices. When energy prices fluctuate,production arrangements will add a constraint. This will be an expansion of the production planning theory.First of all, this paper analyzes the impact of the current background of energy prices on the enterprises,and points out the significance of this paper. Secondly,this paper puts forward the modeling problem of Dynamic Electricity Price Oriented Production Plan (DEPOPP), and designs the overall scheme. The production planning optimization model is established to reduce the cost of electricity and shorten the product waiting time. In this paper, the model is analyzed and the algorithm based on dynamic programming is proposed to solve the optimization model of production planning. The algorithm is used to analyze several typical time-varying electricity price models, and then the important dimension conversion parameter in the model is analyzed. Finally, the core algorithm of the paper is used to design the optimization tool system, the key function realization is designed in detail, and the operation example of the tool is introduced.In this paper, an optimization model with power cost and waiting time is established, and the algorithm is proposed based on the idea of dynamic programming.The validity of the algorithm is proved by results and comparison. The model of production planning here is mainly theoretical research, only considering the time cost and power cost. If we consider more such as labor cost, inventory cost and so on,the model needs to be further adjusted, but the algorithm proposed in this paper still has a reference function. In practice, pay attention to the actual parameters of the model settings is needed.