The data collection relies as the major problem while deploying the sensor nodes in Wireless Sensor Network (WSNs). The collection of data using Mobile Sink (MS) is an effective approach to rectify issues in data collection. In this research, the collection of data takes place using the proposed Multi-Objective Osprey Optimization Algorithm (MOOA) which helps in effective routing strategy and the selection of Cluster Heads (CHs). The optimal CH is selected by considering the fitness functions such as total energy consumption, residual energy, number of packets transmitted and average delay. Similarly, the routing path is selected by considering the fitness functions such as energy consumption and delay. The experimental results exhibits efficiency of suggested framework when it is evaluated with Hybrid Butterfly and Ant Colony Optimization with Mobile Sink (HBACM). The delay of the proposed MOOA for 100 nodes is 9.25 ms which is comparably minimum than with delay of 10.12 ms.