A hybrid binary harmony search algorithm inspired by ant system

Harmony Search (HS) algorithm, which mimics music improvisation process, has been used to solve various optimization problems. However, the standard HS algorithm is not suitable for settling binary-coded problems as the pitch adjusting operator is degraded and cannot efficiently perform the local search in the binary space. To extend HS to solve the binary-coded problems more effectively and efficiently, a novel binary Ant System Harmony Search (BASHS) algorithm is proposed in this paper which is inspired by the search mechanism of Ant System. The new harmony memory consideration operator and pitch adjustment operator are developed to execute the global search and local search with the current iteration best solution and the global best solution. The experiment results demonstrate that the proposed BASHS algorithm is a powerful optimization tool and outperforms binary HS, binary Ant System and Discrete Binary Particle Swarm Optimization algorithm in terms of search accuracy and convergence speed.

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