Wireless rechargeable sensor networks are integral component of IoT where longevity of the network is ensured by recharging sensors through mobile charger periodically or on-demand. However, determining a path schedule of mobile charger that optimizes resources like energy and cost simultaneously is a NP-hard problem. Hence, meta-heuristic algorithms are used to find a solution. The paper presents a new MJaya meta-heuristic algorithm and applies it to solve the problem of mobile charger path scheduling. The MJaya algorithm improves the solution in each iteration towards best value avoiding local optima trap. The median is used in place of mean to deal with outliers’ influence while computing best value. A non-linear objective function is proposed that minimizes latency and maximizes energy uses efficiency simultaneously. Large-scale simulation experiments are conducted to evaluate the performance of MJaya and its comparison with three other counterparts. It is observed that MJaya algorithm results in low latency and thus better performance.