The network function virtualization (NFV) technology can significantly reduce the capital expenditure and improve the flexibility of network serves. The virtual network function (VNF) deployment problem is one of the key problems that should be addressed in NFV. A global constrained optimization model is established to minimize the maximum index of the used frequency slots, the number of used frequency slots, and the number of initialized VNFs,thereby solving the issues of routing and VNF deployment for service chains in inter-datacenter elastic optical networks. VNFs are divided into VNFs with and without dependency,respectively. To ensure the effectiveness of the proposed model, an efficient genetic algorithm based on highly efficient encoding, crossover operators, and mutation operators is designed. Several simulation experiments are conducted using different network topographies with different parameters. The experimental results denote that the proposed algorithm can obtain improved routing and deployment schemes for service chains in the VNF when compared with other algorithms.