Service Composition and Optimal Selection of Low-Carbon Cloud Manufacturing Based on NSGA-II-SA Algorithm

As a new model of networked manufacturing services, cloud (CMfg) aims to allocate enterprise resources, realize rational utilization and adapt increasingly complex user needs. However, previous studies on service composition optimal selection (SCOS) in CMfg environments do not incorporate carbon emissions into the quality (QoS) evaluation indicators. Therefore, SCOS for under low-carbon environment is firstly proposed this paper. Secondly, based Non-dominated Sorting Genetic Algorithm (NSGA-II) algorithm, hybrid multi-objective evolutionary named NSGA-II-SA solve obtain Pareto solution set. Then, an algorithm result optimization strategy combining subjective objective filter set, so as make final decision. Finally, taking natural gas cylinder head production example, compared with other algorithms, results show that can more non-dominated solutions, solutions four dimensions better than other. it proved has comprehensive performance environment.