Optimization problems throw a challenge to designers, as they need to handle with utmost care and swiftness without comprising the accuracy. In the last two decades, the application of nature inspired algorithms is increased for solving engineering problems. Marine Predator Algorithm (MPA) is one of the nature-inspired algorithms that mimics the behavior of marine predators and preys through their mathematical implementation. Sometime this algorithm lacks in fast convergence and exhibits sluggishness in convergence. To improve this virtue, a new bridging function has been proposed in the paper, which is based on the exponential term. In addition, an iteration diversity-based probability switch has also been incorporated to support swift exploitation phase. The modified algorithm is named as the adaptive switch enabled marine predator algorithm (AMPA). The Validation of the implementation of these functions on MPA is carried out with the help of CEC-20 functions. Various analyses and tests are performed, and a comparison with some recently published algorithms has been made. The results affirms superior optimization capability.