The Optimization of Manufacturing Resources Allocation Considering the Geographical Distribution

Abstract

From the perspective of the geographical distribution, considering production fare, supply chain information and quality rating of the manufacturing resource (MR), a manufacturing resource allocation (MRA) model considering the geographical distribution in cloud manufacturing (CM) environment is built. The model includes two stages, preliminary selection stage and optimal selection stage. The membership function is used to select MRs from cloud resource pool (CRP) in the first stage, and then the candidate resource pool is built. In the optimal selection stage, a multi-objective optimization algorithm, particle swarm optimization (PSO) based on the method of relative entropy of fuzzy sets (REFS_PSO), is used to select optimal MRs from the candidate resource pool, and an optimal manufacturing resource supply chain is obtained at last. To verify the performance of REFS_PSO, NSGA-Ⅱ and PSO based on random weighting (RW_PSO) are selected as the comparison algorithms. They all are used to select optimal MRs at the second stage. The experimental results show solution obtained by REFS_PSO is the best. The model and the method proposed are appropriate for MRA in CM.