Study On Job-shop Scheduling System For The Projectile Machinery Manufacturing Companies

The production mode of projectile machinery processing companies has changedfrom small varieties, single batch or multispecies with small batch in the past tomultispecies with various batches now. Such production model makes it possible for thecompany to adjust resource allocation quickly and make overall arrangement of theproduction tasks, improving the utilization efficiency of the machines.This article studies on the production mode of multispecies with various batches inthe projectile machinery manufacturing companies. In order to solve this kind ofNP-hard problems of the Job-shop scheduling, this article proposes the new idea ofintegrating the genetic algorithm and Simulated Annealing algorithm and Tabu Searchalgorithm, and designs two mechanisms called Simulated Annealing–Crossmechanism and the Tabu Search–Variation mechanism, improving shortcomings ofthe single cross and mutation mechanism in the traditional Genetic Algorithm with suchintegration. Finally the GA-SA-TS Hybrid Genetic Algorithm is formed and it isapplicable to solve the Job-shop Scheduling problems. The GA-SA-TS Hybrid GeneticAlgorithm, making three algorithms complement each other, avoids the geneticalgorithm’s shortcomings in poor local search capability and precocious convergence.Then, proceed the simulation on actual JSSP with this hybrid genetic algorithm. Theresults indicate that GA-SA-TS hybrid genetic algorithm, for solving the JSSP, isfeasible, and the quality is improved.Finally VC is introduced to design interface of the software, thereby thevisualization and interaction of software were realized. And again Job-shop productionis simulated with one actual example, proving the availability and practical applicabilityof the GA-SA-TS Hybrid Genetic Algorithm for the Job-shop scheduling of theProjectile Machinery Processing companies.