Distance Maintaining Compact Quantum Crossover Based Clonal Selection Algorithm

Abstract

Premature convergence is one of the major difficulties with Clonal Selection Algorithm (CSA). It has been observed that this problem is closely tied to the problem of losing diversity in the population. In this paper, we propose a distance maintaining compact quantum crossover based CSA. The compact quantum crossover is useful for information exchanging between different solutions, whereas uses fewer antibodies. On the other hand, distance maintaining scheme permits the algorithm to fine tune its solutions. Simulation results on Traveling Salesman Problems (TSP) show that the novel algorithm is able to effectively balance exploration and exploitation of the search space and can also present the optimal or near-optimal solutions.