Mobile adhoc network (MANET) contributes to a variety of applications due to its optimum design and capacity to be used in situations where establishing a physical network is not feasible. MANET consists of nodes that use routing protocols to send packets from source to sink using the store-and-forward technique. Data packet transit from source to sink is a relatively expensive procedure because these packets are delivered through each intermediate node. MANET has a number of issues, one of which being high energy consumption (EC). The wireless mobile nodes in MANET does not have a reliable power source as the nodes in this network are battery-powered. As a result, the network's lifespan is decreased by the quick battery depletion. However, when determining a path from a source to a sink node, traditional protocols also neglect the consumption of energy by the nodes. Therefore, to enhance the performance of MANET routing performance, we proposed an optimized routing protocol named as adhoc on-demand multipath distance vector sleep scheduling particle swarm optimization (AOMDV-SSPSO) which is based on the concept of Swarm intelligence (SI). SI approaches are based on the concept of optimization and provides the best solution in MANET to resolve computational challenges i.e., routing of data using these optimization techniques improves the route optimization and quality of services. The objective of the proposed research work is achieved by three vital steps which are route establishment phase, optimal path selection and sleep scheduling mechanism. The route establishment phase is based on an AOMDV routing protocol which can be used to identify multiple routes for data transfer from source to destination. Out of all the possible routes the optimal path will be selected with the help of particle swarm optimization (PSO). The sleep scheduling technique places nodes in a sleep state when they are not in use and their absence does not result in partition in their immediate area. The effectiveness of the suggested algorithm is examined and compared against the existing approaches in terms of end-to-end (E2E) delay, energy consumption (EC), network lifetime and throughput (TH). The simulation results generated by the network simulator (NS 2.35) software indicate the effectiveness of the proposed technique. According to the simulation results, AOMDV-SSPSO offers greater TH and is more energy efficient, resulting in a longer network lifespan. However, because of the nodes transition from one state to another, the E2E delay in AOMDV-SSPSO is high. In general, it is observed that the proposed technique AOMDV-SSPSO outperforms than other existing protocols.