The Application And Research Of Improved Hybrid Particle Swarm Optimization In Job Shop Scheduling

In the manufacturing industry,in order to get more profit,there is always a problem for enterprises to overall consider about how to improve production efficiency while reducing production costs,maximize the utilization rate of equipment,and adjust production resource allocation rationally.The production scheduling problem as one of the core contents of enterprise production management,studying the scientific and effective scheduling scheme has a positive effect on the production management and production efficiency of the enterprise positively.Job-shop Scheduling Problem(JSP)belongs to the production scheduling problems,which is recognized as one of the more difficult combinatorial optimization problems.Therefore,how to find a more effective and more optimized methods to solve JSP is always the research hotspots for many experts and scholars in the field of intelligent optimization.Particle Swarm Optimization Algorithm(PSO)is simple in principle,easy to operate and stable in process.It is one of the most popular heuristic algorithms due to its global search characteristics of solution space and implicit parallelism solving thoughts.It takes the minimum completion time of JSP as the research background of this paper.Inspired by Migrating Birds Optimization Algorithm(MBO),this paper try to mix PSO and MBO together to improve the local search capability and find the better local and global optimal solutions to enhance the guiding role of each generation of particle flight process,and improves the efficiency of PSO optimization finally.In this paper,The MBO,mixed in the PSO that updates the local extremum of the individual as well as the global extremum of the population by adjusting the information level of the single individual in the solution space to perceive the other individuals in the V-shaped formation of the common flight,and adjusting the flight state in time,thereby broadening the search range and getting a better solution.The new algorithm is applied to JSP,and it is simulated and tested by using standard test set.The results show that the new algorithm has a better performance.Finally,in order to prove the practical significance of the algorithm,combined with the author's improved hybrid particle swarm optimization algorithm(IHPSO),a workshop scheduling system is developed based on the actual production workshop of a certain machine processing plant,which has achieved good practical application results.