| Citation: | DING Tao, YAN Guangrong, LEI Yi, et al. A method of multi-level manufacturing service modeling and combinatorial optimal-selection[J]. Journal of Beijing University of Aeronautics and Astronautics, 2019, 45(7): 1398-1405. doi: 10.13700/j.bh.1001-5965.2018.0630(in Chinese)
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In order to improve the accuracy of service modeling and combinatorial optimal-selection in cloud manufacturing, a multi-level modeling methodology is proposed to describe manufacturing services, which subdivided the service into three fine-grained levels:resource service, function service and process service. From the perspective of QoS indexes, the relationship among execution, time service cost and user evaluation for different service levels are analyzed and elaborated, and the corresponding evaluation objective functions of services composition are established. A niching behavior based gravitational search algorithm (NGSA) is designed to address manufacturing services composition problem, in which the niche crowding factor and fitness sharing technology are applied to gravitational search algorithm (GSA) to improve its convergence speed and accuracy. Finally, the simulation research results demonstrate that the NGSA algorithm can search better solution with less time-consumption than the traditional algorithms such as genetic algorithm (GA) and particle swarm optimization (PSO) algorithm.
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