Abstract
To find out the best part machining service provider combination, the theory of multiple objective optimization is discussed in detail via mathematic formulation. Relationships among service provider candidates, service types and parameters are analyzed and uncovered by matrix accumulation. The evaluation index and the practical strength are defined as parameters’ functions. Typical evaluation indexes, such as assembly quality and cost, are chosen to be analyzed in detail, and dimensionless method is put forward to combine them together. A problem-solving algorithm is designed on the basis of the particle swarm optimization. An example is presented to validate that the proposed methods is efficient in solving the multiple objective optimization of the part machining service provider combination problem.
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