The Production Scheduling Problem Of Foaming Production Workshop

Production scheduling system is a very important part of the production managerment system of manufacturing enterprise. Production scheduling system play a large role in reducing production cost, shortening production cycle time, ensuring the delivery date and so on. So the production scheduling problem(PSP) has always been a research hot issue. Most of the research of PSP are about the typical ones, but the actual PSP is generally more complex, may not belong to any of the typical ones. In this paper, it study the PSP of foaming production. It does not belong to the classical scheduling problem, but there are many PSP which are similar to it in the real product workshop. So studying the PSP of foaming production has a certain research significance.In this paper, based on the freezer door foaming shop of a manufacturing enterprise, the PSP of the foaming production was investigated. According to the characteristics of foaming production scheduling problem, the problem sloving is divided into two stages, the basic optimization stage and the replacing-mould optimization stage, and established the mathematical model of the two stages respectively. Considering the characteristics of many intelligent optimization algorithms, genetic algorithm and tabu search algorithm are used in this paper. Considering the solution space of the basic optimization stage is much larger than the replacing-mould optimization stage’s, it improved the genetic operations in the basic optimization stage when genetic algorithm was used for solving the PSP. Selection operation and crossover operation apply competition mechanism, to avoid the loss of excellent genes. To make a more diverse population, mutation operation set up several mutation points. The characteristics of the actual PSP was fully considered when tabu search algorithm was used for solving the problem. First improved the generation of the initial solution, to make the local search performance of tabu search algorithm be fully used. Then the output solution was choosed from the whole operation process of the algorithm, to make sure the output solution is the optimal solution.In the final chapter, the two algorithms was used to solve several actual examples of the PSP. The mode of the foaming production is multi-varieties and small batch, so the examples is typical ones. First according to the examples, the key parameters of the two algorithms was setted respectively. Then used them to solve the PSP. From the comparative analysis of the results, It can be seen that tabu search algorithm is more suitable for the PSP. Compared with genetic algorithm, tabu search algorithm can get the optimal solution more steady. And also Analyzed the reasons from the Angle of the algorithm itself.