Research On Interval Programming Model Of Resources Optimal Scheduling In Manufacture Grid

With economic globalization, great changes have occurred in manufacturing. In order to respond to the market in a faster, better and more efficient way, manufacturing enterprises have to make full use of resources around the world and integrate the manufacturing resources dynamically and optimally. In this case, Manufacturing Grid (MG) is proposed. The goals of MG are sharing resources and working together, so the resource-optimal scheduling in Manufacturing Grid is a key and hot issue. According to the characteristics of interval of the key parameters(resource prices and task cost constraints),which impact resource-optimal scheduling,this paper discusses how to rationally allocate resources to different tasks to meet user's requirements, the main research work are as follows:1. Analysis of resource scheduling in MG. Discussing the characteristics of resources and tasks, describing Batch mode and Online mode of resource scheduling, this section points out the uncertainty of resource scheduling and that resources optimal scheduling is an interval programming problem.2. Interval Programming Model of resource-optimal scheduling in Online mode. When a resource or task is arriving, Intermediate Node (IN) immediately searches the resource or task which meets the requirements from its repository. According to the characteristics of interval of the key parameters,which impact resource-optimal scheduling,this section establishes task-oriented and resource-oriented scheduling models based on interval.3. Interval Programming Model of resource optimal scheduling in Batch mode. Many resources and tasks arrive at IN who gives the overall optimization in a period. According to the characteristics of interval of the key parameters, this section establishes Interval Programming Model.4. Design and Implementation of the models of manufacturing resource optimal scheduling. IN can adjust the prices of resources and cost constraints of the tasks through changing the size of the risk factors, and find a more suitable scheduling scheme.