Artificial bee colony (ABC) algorithm is one of the efficient meta-heuristic optimization algorithm, based on bee behavior for food searching. In order to improve the exploitation ability of ABC algorithm, an elitism based exploitation strategy is incorporated in ABC and the proposed variant is named as Elitism Based ABC Algorithm (EbABC). In the proposed search strategy, the step sizes of the solutions during the solution search process depend on a weighted component, calculated by using three best solutions of the swarm. Further, in order to compensate the exploration, a global search ability is introduced in scout bee stage. To analyze the performance of EhABC, it is applied on 15 standard benchmark functions and the results are compared with some significant variants of ABC. The analysis of the results shows that the proposed EbABC Algorithm is a competitive variant of ABC algorithm.