The growth of mobile device technologies has given rise to widespread applications that led us to economic wireless networks, including with and without infrastructure. Efficient routing with Quality-of-Service (QoS) constraints is a challenging issue in substantial infrastructure-less and dynamic networks. To improve QoS constraints for such a network is an NP-complete problem. It is observed that Particle Swarm Optimization (PSO) is one of the most potent swarm-based optimization techniques to solve NP problems. Hence, PSO is chosen to boost QoS constraints and provide more reliable routes than existing ondemand routing protocols. This paper has proposed a PSO-based routing facility that uses a dynamic queue mechanism for efficient routing considering enriched QoS constraints. The uniqueness of the proposed technique is selecting the fitness function that is dynamic in nature and determined based on the data obtained by the successor node. The queue size is maintained dynamically to minimize the data drop. The simulation results revealed that the proposed algorithm performs better than the existing conventional algorithms like Adhoc On-Demand Distance Vector (AODV), Destination-Sequenced Distance Vector Routing (DSDV), and metaheuristics like ACO, PSO, QoRA, Enhanced-Ant-AODV, and Cuckoo Search Optimization AODV (CSO-AODV) in terms of packets sent, packets received, PDR, end-to-end delay and routing overhead.