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Bi-direction quantum crossover-based clonal selection algorithm and its applications
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DOI：10.1016/j.eswa.2014.05.053.png)
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Abstract
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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. (C) 2014 Elsevier Ltd. All rights reserved.
Keywords:
Clonal selection algorithm
Bi-direction quantum crossover
Traveling salesman problem
Holes machining path planning problem
Multi-objective optimization
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