Design And Application Of Multi-Objective Hierarchical Planning Production Scheduling Algorithm

With the intelligent manufacturing information system gradually entering the workshop,the research on the scheduling scheme more suitable for the actual production of the company is also in full swing.The workshop processing in the new era has become more flexible,diversified objectives,abundant resources and personalized demand are the main characteristics of today’s discrete production workshop.Although the scheduling idea has been put forward as early as the 1960 s,it has been gradually popularized and used in factories after nearly 60 years of development.The intellectualization of the scheduling process provides great convenience for the production workshop.In this paper,the multi-objective production scheduling problem faced by machining enterprises under multiple constraints such as double stations,adjacent equipment and outsourcing processes is analyzed.Taking the conditions such as the shortest completion time,equipment continuity and on-time delivery as the target object,the hierarchical programming theoretical model is established,and the weighted combinatorial optimization method is used to transform the multi-objective into a single objective function,It is conducive to algorithm design and solution.Then,using the idea of genetic algorithm,digital symbols combined with three-stage coding method are used to intuitively express chromosomes,which is convenient for later decoding operation.By dynamically adjusting the crossover and mutation probability to ensure the global optimization and accelerate the later convergence speed,the concept of fission molecule is proposed for the two station problem in production equipment,and the chromosome offset is used to improve the compactness of scheduling results.For the bottleneck process problem,the idea of combining forward and reverse scheduling is adopted to shorten the production cycle and reduce the inventory cost.In order to achieve equipment load balance,the dispatching priority is dynamically adjusted to prolong the service life of the equipment.Finally,an example is given to prove the effectiveness of the algorithm design.After several examples,the population size,iteration times and other parameters of the genetic algorithm are determined,and the variance is calculated by using the results obtained many times to test the stability of the system design.Through rough scheduling to solve business logic problems,hierarchical processing of actual production problems,the improved algorithm is compared with the traditional genetic algorithm,showing the advantages of the improved genetic algorithm,which is applied in actual production and greatly improves the production efficiency.