Bat algorithm (BA) has been widely used to solve the diverse kinds of optimisation problems. In accordance with the optimisation problems, balance between the two major components: exploitation and exploration, plays a significant role in meta-heuristic algorithms. Several researchers have worked on the performance for the improvement of these algorithms. BA faces one of the major issues in high dimensions. In our work, we proposed a new variant of BA by introducing the torus walk (TW-BA) to solve this issue. To improve the local search capability instead of using the standard uniform walk, torus walk is incorporated in this paper. The simulation results performed on 19 standard benchmark functions depicts the efficiency and effectiveness of TW-BA compared with the traditional BA, directional bat algorithm, particle swarm optimisation, cuckoo search, harmony search algorithm, differential evolution and genetic algorithm. The promising experimental result suggests the superiority of proposed technique.