Abstract

ABSTRACT With the development of new technologies, cloud manufacturing system allows users to request different services by providing a customer-oriented structure with the possibility of access to distributed manufacturing resources. By departing from literature, this study relaxes the unreasonable assumption that all tasks are available at the first moment of scheduling. In addition, two factors are considered to get the model closer to reality: (1) The time/cost of sub-tasks transfer among different services of enterprises in diverse geographical locations; and (2) Service setup time/cost to perform diverse sub-tasks on a given service consecutively. Taking into account these characteristics, a model including three objects of cost imposed on the cloud manufacturing system, task completion time and service quality is developed. The results confirm the importance of considering task arrival time, logistics time/cost and setup time/cost to get more realistic solutions. GAMS software is employed to solve the problems with small and medium scales while a solution approach method based on a genetic algorithm is developed to solve the problems on a large scale. And finally, a sensitivity analysis is undertaken to gain insight into the impact of time, cost and user’s requirements on the final solution.

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