摘要：
Quantum-Inspired Evolutionary Algorithm (QEA) has been shown to be better performing than classical Genetic
Algorithm based evolutionary techniques for combinatorial optimization problems like 0/1 knapsack problem. QEA
uses quantum computing-inspired representation of solution called Q-bit individual consisting of Q-bits. The probability
amplitudes of the Q-bits are changed by application of Q-gate operator, which is classical analogous of quantum rotation
operator. The Q-gate operator is the only variation operator used in QEA, which along with some problem specific heuristic
provides exploitation of the properties of the best solutions. In this paper, we analyzed the characteristics of the QEA
for 0/1 knapsack problem and showed that a probability in the range 0.3 to 0.4 for the application of the Q-gate variation
operator has the greatest likelihood of making a good balance between exploration and exploitation. Experimental results
agree with the analytical finding.
