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Network Function Virtualization addresses the defect of traditional middleboxes and enables operators to implement new services through a process named Service Function Chain mapping. Service Function Chain is composed by a sequence of Virtual Network Functions (VNFs) which is deployed in shared platforms. Service Function Chain with parallel VNFs is proposed to reduce the delivery latency. In this paper, a multiple instances mapping scheme named MIM is proposed to resolve the performance bottleneck introduced by the imbalance of parallel VNFs. A integer programing model is established to describe the multiple instances mapping problem based on queuing theory, and a double layer Genetic Algorithm is used to allocate parallel VNFs with multiple instances. Simulation results show that the multiple instances mapping scheme can improve the performance of Service Function Chain with parallel VNFs effectively.