A Hybrid GA-TS Algorithm for Optimizing Networked Manufacturing Resources Configuration

In recent years, more and more researchers have focused on various significant issues of resource configuration, such as maximum computing performance and minimum response time, especially taking existing resource utilization into account. The goal of this research is to design a resource configuration optimization system under networked manufacturing environment. A prediction mechanism is realized by using support vector regression (SVR) to estimate resource utilization according to network protocol of each manufacturing process, while redistributing resources based on the current status of existing resources pool. A resource configuration mechanism applying genetic algorithm working along with the tabu search process (GA-TS) is proposed in this study to determine the redistribution of resources. The experimental results show that the proposed scheme achieves an effective configuration via reaching the balance between the utilization of resources within existing resources and network protocol of each manufacturing process between potential resource requirements and the network resource providers.