<p>Clustered Wireless Sensor Networks (WSNs) help in the construction of robust and scalable network infrastructure which increases the probability of minimizing energy consumption with extended network lifetime. But the clustered WSNs pose the challenges of non-uniform energy consumption, inadequate cluster head allocation and imbalanced distribution of load in the network. This challenges dramatically impact the network lifetime when improper clusters are constructed. This improper clusters in turn makes the sensor node to prematurely die due to increased energy consumption. Potential cluster formation and optimal cluster head selection techniques are essential for the purpose of improving the clustering quality that contributes towards better energy stability and extended network lifetime. In this paper, Boosted Sooty Tern Optimization Algorithm-based protocol with multiple objectives (BSHPFMOCS) is proposed for enhancing the quality of clustering with the objective of improving energy stability and prolonged network lifetime in clustered WSNs. This BSHOA facilitates an accurate search process which helps in selecting optimal CHs depending on the fitness function that concentrates on the improvement of clusters’ aggregation. This clustering protocol incorporated an advanced cluster formation strategy which entrusted the CHs to select their own cluster members depending on minimized intra-cluster distance. It further included Piranhav Foraging Optimization Algorithm (PFOA) for employing sink mobility that addresses the problem of hot-spot in WSNs. The simulation results of BSHOA protocol confirmed better network lifetime of 10.76%, improved throughput of 18.42% with reduced packet delay of 20.86%, and minimized energy consumption of 21.94%, compared to the baseline clustering protocols used for investigation.&#xa0;</p>