Bi-direction quantum crossover-based clonal selection algorithm and its applications

• A bi-direction quantum crossover inspired by the principle of quantum mechanics is proposed.
• The algorithm is tested on the holes machining path planning optimization problem.
• The algorithm achieves a good balance between exploration and exploitation.
• The proposed algorithm outweighs other clonal selection algorithms.

In order to improve the performance of quantum interference crossover, a bi-direction quantum crossover is proposed based on the quantum jump theory. The proposed crossover is inspired by the principle of quantum mechanics. That is, when an electron drops from a higher energy level to a lower energy level, energy is released by the atom. Also, energy is absorbed when it moves from a lower energy level to a higher energy level. The bi-direction quantum crossover is combined with clonal selection algorithm (CSA) to further enhance the performance of CSA. The effectiveness of the method is tested on a class of traveling salesman problems (TSP) and engineering practical problems of holes machining path planning (HMPP). Experimental results show that the proposed algorithm achieves a good balance between exploration and exploitation, and outweighs other CSAs and heuristic algorithms in terms of convergence speed and robustness.