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A new ant colony optimization algorithm for the multidimensional Knapsack problem
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AICI'11 Proceedings of the Third international conference on Artificial intelligence and computational intelligence - Volume Part III
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This paper proposes a novel quantum-inspired pseudorandom proportional evolutionary algorithm (QPPEA), whose core is that the pseudorandom proportional operation is introduced in the update strategy. As the traditional quantum evolutionary algorithm (QEA) generates the binary solution completely depending on the probability and the amplitude of rotation angel is small, the efficiency of QEA is low. To make up for it, pseudorandom proportional operation inspired by ant colony algorithm is introduced in QPPEA. Further more, for the sake of the introduction of pseudorandom proportional operation, quantum mutation operator based on quantum NOT gate is used to keep the diversity of population. The simulation results on a class of the multidimensional knapsack problems (MKP) demonstrate that QPPEA can effectively enhance the searching efficiency and improve the optimization performance.