Study On Production Scheduling Optimization For Make-To-Order Enterprises

Production Scheduling is central issue for management of modern enterprises. It has been paid much attention in manufacturing systems and it is one of the most difficult problems in theoretical research. When enterprise resource is restricted, the target of Production Scheduling is to determine the Processing order and processing times on every machine for all of products so that the most optimal production target can be reached.The complexity, dynamics and abrupt change make manufacturing process be a long haul when depending on person only. And it is unrealistic to rely on computers. So person, computer and intelligent technology must be combined organically when studying production scheduling problems. This is the important content of this paper.To printing and dyeing enterprises, the production scheduling problem is combinatorial optimization problem with discrete variables. And it is a typical shop scheduling problem. But the production process is complicated and changeable of this type of enterprise. Although most of tasks belong to flow shop scheduling, a small part of those belong to job shop scheduling. Based on the practice of the project, this paper establishes corresponding HTCPN models and simulates the production process after investigating and analyzing the production process of some printing and dyeing enterprise deeply; Next, flow shop scheduling, hybrid flow shop scheduling are studied and corresponding mathematic programming models are established; Then, some algorithms that usually be used to solve the optimal problems are compared. In this paper, traditional genetic algorithm and particle swarm optimization algorithm are investigated and they have been changed and improved based on real facts. At the same time, matlab software is used to implement and test these algorithms. At last, .net program is programmed to apply to production scheduling of printing and dyeing enterprise. The Gantt Charts are generated in programs and scheduling is achieved.According to practical experience, this paper pursues the researches and performs analyses from user's perspective definitely and achieved the anticipated results. At the same time, this paper verifies that PSO algorithm which can solve continuous-variable problems effectively can be used to deal with discrete-variable problems theoretically and in practice.