For Rapid Manufacturing Shop Floor Scheduling Strategy

The insufficience of resources in the shopfloor holds back the accomplishment of production plans. In a sense, whether the enterprise can survive market competition is determined by whether it can meet customers' demands in time, which is further determined by how efficiently the limited resources are used. Consequently, extensive researches have been carried out concerning scheduling methods for shopfloor since scheduling methods help make best use of resources.In real shopfloor scheduling scenarios, resource restriction coexists with process restriction, which makes shopfloor scheduling problems NP-hard. Meanwhile, the changeability of market demand together with the uncertainty in a real job shop adds to the complexity of JSSP. As a result, there exist no effective and widely applicable job shop scheduling methods.This paper puts forward a MAS-GA based dynamic job-shop scheduling model. Our scheme combines the advantages of GA and MAS, taking into consideration the characteristics of the PULL Pattern market. Based on the model, we implemented an effective and widely applicable prototype system for dynamic JSSPs.The first part of the paper introduces the background, the categories and the development of job shop scheduling. Meanwhile, the promising aspects of GA and MAS for solving NP-Hard problems are highlighted. The second chapter analyses in detail how to adapt GA for JSSP, and compares the performances of the GA in binary coding and decimal coding. Also, we put special emphasis on deadlock problems since deadlock is a big obstacle to GA-based JSSP solutions. Considering GA converges slowly, special adaptations are made to the GA constructed in the second chapter. The new GA converges much more quickly and can find the most suitable route for an operation. The fourth chapter introduces MAS mechanism to construct a dynamic job-shop scheduling system, with GA providing basic support. MAS mechanism decomposes a continuous and dynamic job-shop scheduling problem into series of JSSPs so that the predefined GA can work out the schedule. Finally, the results from simulation shows the MAS-GA based scheduling system is promising for practical job-shop scheduling.