Optimal selection of cloud manufacturing resources based on bacteria foraging optimization

As a service-oriented manufacturing paradigm, cloud manufacturing (CMfg) combines the computing resources the manufacturing resources respectively from the Internet and enterprises into a huge shared resource pool for network-based distribution of manufacturing resources and manufacturing tasks. In order to reduce the number and complexity of resource pools in CMfg, it is necessary to simplify the process, save manufacturing resources, shorten the production time and improve the productivity of enterprises. Therefore, a method for the optimal selection of cloud Manufacturing resources based on bacterial foraging optimization was proposed in this paper. First, a scheme evaluation system based on the evaluation factors of production cost, production time and processing quality was established, and a mathematical model of resource optimization selection was built. Secondly, a combination of Analytic Hierarchy Process (AHP) and entropy weight method was used to obtain the weights of different evaluation indicators, and a bacterial foraging optimization algorithm (BFO) was used to optimize the scheme. Finally, an example study of the method was conducted with the NGW51 reducer as an example. By comparing with existing methods, the experimental results verify the advantages of BFO in CMfg resource optimization selection.