Implement a soa resource scheduling framework for multi-plants

Traditionally, multi-plants resource scheduling problems have often been focused on improving efficiency of resolving in the literatures. However, it is difficult to acquire model variables in heterogeneous environments practically. In this work, we attempt to achieve two goals that (1) optimize mathematical model, (2) execute mathematical model with various variables in heterogeneous environment. In order to effectively resolve the issues mentioned above, we presented a Serviced-Oriented Architecture (SOA) framework to integrate resource scheduling problem for multi-plants. In our previous works, we proposed an energy function for the Hopfield neural network (HNN) in Computational Intelligence area. In this paper, the energy function is modified to describe the resource scheduling problem for multi-plants. In addition, the proposed SOA framework attempts to overcome the barriers to achieve seamless integration. The framework consists of a numbers of Web-Services and all Web-Services are managed and executed by BPEL engine. The framework is implemented as a prototype system, which is made up of five types of Web-Services. Web Services Planning Service is responsible to plan and generate BPEL script. Mathematical Model Services illustrate the information of multi-plants model, Variables Acquire Services are responsible to acquire variables of model in heterogeneous environments, and Common Services interact with decision maker of multi-plants resource scheduling. Moreover, Resource Scheduling Services implement the particle swarm optimization, and are responsible to accomplish the optimization of multi-plant scheduling model. In conclusion, the SOA framework provides the flexibility as required for the integral management of mufti-plants business environments and the availability for resource scheduling.