Study on multi-task oriented services composition and optimisation with the ‘Multi-Composition for Each Task’ pattern in cloud manufacturing systems

Recently, cloud manufacturing has been generating a great deal of interest among both practical users and researchers. Multi-task oriented manufacturing cloud services composition and optimisation MTO-MCSCO is critical to the optimal allocation of manufacturing resources and capabilities in cloud manufacturing systems. However, if users’ QoS requirements on multi-functionality manufacturing tasks MFMTs are high enough, no competent composite services can be identified based on the concepts of the single-task oriented services composition and optimisation STO-SCO technique, which was previously in use, and the currently existing ‘Each Composition for Each Task’ ECET pattern. To circumvent this, a ‘Multi-Composition for Each Task’ MCET pattern based global approach is proposed to combine the incompetent composite services into a whole to perform each MFMT collectively, in order to ensure the success rate of QoS requirement fulfilment and the overall QoS outcome. This new issue of MTO-MCSCO with the MCET pattern is a more general problem than are the previous STO-SCO and the current ECET pattern. To formulate the problem, exterior aggregation patterns and formulas are proposed. To tackle the problem, a hybrid-operator based matrix coded genetic algorithm HO-MCGA is implemented. The experimental results indicate that the proposed MCET pattern based global approach significantly outperforms the previous approaches, and the proposed HO-MCGA is sound performance-wise.