Elephant Search Algorithm (ESA) is one of the contemporary meta-heuristic search algorithms recently proposed. The male elephants are responsible for global exploration, roaming to new dimensions of search space. The female elephants focus on doing local search, for finding the optimal solution. The lifespan mechanism design makes the whole group born and die dynamically thus helps inherit good information from ancestors as well as escape from local optimum. However, in the naive lifespan mechanism of ESA, search agents expire at equal chances regardless of their current locations. It is supposed that search agents who made improvements in their solutions are more likely to yield better results than those who performed mediocrely. We propose a vitality-based elephant search algorithm called VESA to fine-tune the lifespan of search agents by using a vitality computation mechanism that grant the fit agents longer life at the expense of the mediocre agents' life. With the extra lifespan offered, the fit agents have more time to continue enhancing the solutions. Computer simulation on nine testing functions shows the VESA outperforms the naive ESA in terms of the final tness value.