Research On Production Planning And Scheduling Of Process Industry Based On Improved Collaborative Optimization Algorithm

Production planning and production scheduling are the two cores of operation management and production management of process industrial enterprises,both of which are of great significance for improving the economic benefits and core competitiveness of enterprises.There is a close relationship between production planning and production scheduling.If the two are optimized separately,the results often conflict with each other.Therefore,comprehensive integration optimization should be carried out for the two.The problem after comprehensive integration has multi-objective,multi-constraint and a large number of design variables,so an effective algorithm is urgently needed to solve the optimization of this problem.Based on the collaborative optimization algorithm,this paper studies the optimization of production planning and scheduling in process industry.The main research contents of this paper are as follows;(1)Modeling for complex process industrial production planning and production scheduling.A corresponding production planning model is established in conjunction with the departments involved in the production plan and related costs.A corresponding production scheduling model is established based on the specific content of production scheduling level and process constraints.Coordinate the analysis of the relationship between the two,combined with the idea and structure of the collaborative optimization algorithm,improve the model of production planning and production scheduling,and establish an integrated model of the two;(2)Aiming at the problems existing in the current stage of collaborative optimization algorithm,an improved Collaborative Optimization(ACO)algorithm is proposed.A new step-wise relaxation factor is introduced at the system level,and the dynamic or static relaxation factor is selected by judging the iterative optimization at different stages.Optimizing the initial dynamic relaxation factor can make the overall optimization fast convergence.Optimizing the late static relaxation factor can further accelerate the overall convergence speed,improve the interdisciplinary consistency,and ensure the solution result.By simulating the classic numerical case and the reducer case,the ACO algorithm is compared with the standard relaxed CO algorithm and the dynamic relaxation CO algorithm.The simulation results show that the ACO algorithm can converge quickly and smoothly to the global optimal solution and has better robustness;(3)Combined with the CO-based production planning and production scheduling integration model and ACO algorithm,it is applied to the example of batch chemical companies.The simulation results of different market order quantities are compared with the pure scheduling optimization algorithm and the standard relaxed CO algorithm.The feasibility of ACO algorithm in solving the actual process industrial production planning and production scheduling problem is verified.Efficient.