Research On Optimal Scheduling Method Of Flexible Workshop Production Based On Stackelberg Game

Considering diversified optimization objectives and supply and demand balance in regional integrated energy system will make the transaction scheduling strategy and decision-making mechanism complex and diverse.It is a current research trend to introduce a game mechanism dominated by price to coordinate the balance of interests of different actors.With the development of smart grid and smart manufacturing,there is a trend toward transparency,automation and intelligence between industrial park operators and industrial users.Considering the regional transaction system with the operators of industrial parks and industrial production users as the main body,and the flexible manufacturing workshop as the main industrial user production mode.In this paper,the scheduling problem of FPLs based on Stackelberg game is studied and a game model is established in which the leader is the operator of the industrial park and the follower is the industrial user.Two different optimization solutions are proposed respectively,and the single objective and multi-objective production scheduling problems of flexible workshop with electricity price information are studied.The main research contents are as follows:Firstly,considering the production process of the flexible manufacturing workshop under the incentive of electricity price,the balance between supply and demand in the industrial park and the demand status of the intelligent factory are analyzed,and the main problems in the current production scheduling field are summarized.A flexible manufacturing shop system model based on Stackelberg game is proposed based on TOU electricity price,which provides a theoretical basis for subsequent problem optimization and algorithm design.Secondly,based on the Stankelberg game between the industrial park operator and the industrial users,the industrial park operator is the leader and the industrial users are the followers.The upper level optimization problem which aims at minimizing the power cost of industrial park operators and the lower level optimization problem which aims at maximizing the satisfaction function of industrial users are proposed.The distributed electricity price iterative algorithm and the adaptive production scheduling algorithm are designed to solve the upper and lower level optimization problems respectively.The simulation results show that the algorithm can effectively calculate the optimal electricity price,achieve the balance between the upper and lower level of the game optimization goals,the industrial users can get the maximum satisfaction and the industrial park operators to obtain the optimal power cost.Finally,for the multi-objective flexible shop scheduling problem based on Stangkelberg game,the inverse induction method is used to solve the problem,and the optimal electricity price of each period is obtained,and the electricity price is considered as the incentive in the production scheduling process of industrial users.Industrial park operators consider the electricity cost target as a utility function.Taking the maximum completion time and energy consumption cost as the optimization objectives for industrial users,the second-generation non-dominated sorting genetic algorithm(NSGA-Ⅱ)was used to solve the scheduling process.Finally,the software test interface is designed,which verifies that the multi-objective solution and optimization can be realized in the process of FJP under the electricity price incentive.