Research On Model And Algorithms Of Job Shop Production Scheduling Problem In Carbon Enterprises

With the increasing competition in product manufacturing market,optimizing resource allocation through production management has become one of the key factors for carbon enterprises to gain profits.Starting from the Job Shop Production Scheduling,which is the core of production management in carbon enterprises,this paper analyses and discusses its optimization model and method.The thesis is mainly about the following four aspects,which are as follows:1.The organizational type and characteristics as well as the main content and existing issues of the Job Shop Production Scheduling in carbon enterprises are researched.2.The technical and other constraints of carbon enterprises as well as the optimization target of Job Shop Production Scheduling are researched,and the optimization model of Job Shop Production Scheduling issues is established based on this.3.Through the analysis of the basic principles,optimization mode and parameter characteristics of Particle Swarm Optimization and Ant Colony Optimization.It can be known that both the Particle Swarm Optimization and the Ant Colony Optimization make all the individuals in the population mainly learn the optimal solution of the algorithm iterative process.Although this optimization mode has better global search performance,it is easy to converge locally in the late iteration period.In order to improve the performance of Particle Swarm Optimization and Ant Colony Optimization,and to solve the problem that these are easy to fall into local converge,the research combines the Particle Swarm Optimization and the Ant Colony Optimization improvement strategy,and proposes an improved algorithm that can optimize both the Particle Swarm Optimization and the Ant Colony Optimization.4.Then based on a specific case of optimized arithmetic of Job Shop Production Scheduling issues for carbon enterprises,the Particle Swarm Optimization,the Ant Colony Optimization and the Improved Hybrid Optimization Algorithm are used to optimize the cases and compare the simulation optimization results.The practice proves that compared with the traditional optimization algorithm,the global convergence performance of the Improved Hybrid Optimization Algorithm proposed in this paper is improved to a certain extent compared with the original algorithm,with better optimization effect and certain computational advantages.