Research On Optimization Of Supply Chain Production Planning Of Refinery Enterprises With Uncertain Demand And Production Rate

Overcapacity and technological transformation and upgrading have intensified the competition among refineries.As the gap between refineries in terms of capital,technology and manpower becomes smaller and smaller,the gap is reflected in the management and optimization of supply chain.The optimization of supply chain production planning has become a hot issue.In this paper,supply chain production planning is studied,considering the uncertainty of demand and yield in refinery enterprises.Based on the analysis of supply chain structure and uncertainty in refinery enterprises,it is found that the uncertainty of demand and yield is to study the user demand of different products in different planning cycles and the output of different products under different production schemes in different planning cycles.And probability indirectly describes the impact of uncertainty,that is,the loss cost when the user demand is not satisfied,when the production plan is switched,and when the product inventory exceeds the limit.If we can better control the cost loss and plan change brought by uncertainty to supply chain production planning,we can better improve the effect of supply chain optimization.A production planning model of refinery supply chain with uncertain demand and yield has been established.The objective function is the minimum total cost expectation,including purchase cost,transportation cost,inventory cost,loss cost that user demand is not satisfied,loss cost of scheme switching operation and loss cost of inventory overrun.Under the guidance of two-stage system thinking,the loss function and probability constraints with uncertain demand and yield are set up by using the theory of conditional risk value,and other constraints are adjusted to improve the final model.The heuristic iterative simulation algorithm is used to solve the model,and the production and processing schemes are iterated continuously.Satisfactory solutions are obtained by traversing a few of the most likely production schemes.Monte Carlo simulation statistics and simulation costs are used to determine the reasonable scene sample space,and reference materials are used to determine the appropriate decision-maker control risk threshold.Through an example of S refinery,two scenarios are set up to compare the optimal dispatching between the deterministic model and the model in this paper.It is found that the simulation mean distribution of demand and yield uncertainty model is dispersed and the variance is larger than that of the deterministic model,but the fluctuation shape and amplitude are similar,which proves that the model in this paper is feasible and conforms to the actual production.Iterative simulation shows that the model converges to the 6th iteration,which is the minimum iteration simulation mean,and the corresponding expected target value is the lowest total cost expected target of the model.The 6th iteration production plan sequence is the optimal supply chain production plan of the refinery enterprise.The above verifies the validity and feasibility of the model in solving the supply chain production planning problem under uncertainty.The research methods and ideas in this paper are an extension and extension of the uncertain supply chain problem.