TY  - EJOU
AU  - Yang, Xiaoxuan 
AU  - Fang, Zhou 

TI  - The Cloud Manufacturing Resource Scheduling Optimization Method Based on Game Theory
T2  - Journal on Artificial Intelligence

PY  - 2022
VL  - 4
IS  - 4
SN  - 2579-003X

AB  - In order to optimize resource integration and optimal scheduling problems in the cloud manufacturing environment, this paper proposes to use load balancing, service cost and service quality as optimization goals for resource scheduling, however, resource providers have resource utilization requirements for cloud manufacturing platforms. In the process of resource optimization scheduling, the interests of all parties have conflicts of interest, which makes it impossible to obtain better optimization results for resource scheduling. Therefore, a multithreaded auto-negotiation method based on the Stackelberg game is proposed to resolve conflicts of interest in the process of resource scheduling. The cloud manufacturing platform first calculates the expected value reduction plan for each round of global optimization, using the negotiation algorithm based on the Stackelberg game, the cloud manufacturing platform negotiates and mediates with the participants’ agents, to maximize self-interest by constantly changing one’s own plan, iteratively find multiple sets of locally optimized negotiation plans and return to the cloud manufacturing platform. Through multiple rounds of negotiation and calculation, we finally get a target expected value reduction plan that takes into account the benefits of the resource provider and the overall benefits of the completion of the manufacturing task. Finally, through experimental simulation and comparative analysis, the validity and rationality of the model are verified.
KW  - Cloud manufacturing; resource scheduling; optimal allocation of resources; conflict of interest; stackelberg game

DO  - 10.32604/jai.2022.035368