Cognitive radio sensor networks (CRSN) are severely energy constrained and radio frequency (RF) wireless energy harvesting (RFWEH) has been shown to improve network lifetime. In many CRSN applications, node mobility poses challenges due to changing network topology. In this research, the Adaptive Spider Monkey Optimization (ASMO) algorithm is proposed for obtaining the energy efficient Cluster Head (CH) selection and routing in CRSN. The consumption of energy in CRSN is achieved by the optimal routing method by utilizing the optimization algorithm. The optimization-based clustering and routing approach is developed for designing the optimal transmission path by CH to destination. Key parameters such as energy consumption (EC), packet delivery ratio (PDR), throughput, network lifetime (NL), and end-to-end delay (EED) are employed to evaluate suggested methodology. Comparative analysis shows that the ASMO methodology outperforms present methods in terms of performance.