An imperialist competitive algorithm for service composition and optimal selection in cloud manufacturing

Cloud manufacturing is an emerging service-oriented manufacturing paradigm that integrates and manages distributed manufacturing resources through which complex manufacturing demands with a high degree of customization can be fulfilled. The process of Service Composition and Optimal Selection (SCOS) is an important issue for practical implementation of cloud manufacturing. In this paper, a new Mixed Integer Programming (MIP) model for solving the SCOS with transportation consideration has been proposed. This model minimizes both manufacturing and transportation costs subject to some constraints such as necessity of transportation between manufacturing resources and the requirements specified by customers in terms of maximum cost and delivery date. Then, an Imperialist Competitive Algorithm (ICA) was tailored to solve the SCOS for an example of online motorcycle production in the United States. The results showed that the ICA is able to find the optimal solution faster than the CPLEX solver in GAMS optimization software. The ICA can be applied for solving the large-scale instances of the SCOS problem as well.