Invited Talk: Quantum Computation
VLSID '99 Proceedings of the 12th International Conference on VLSI Design - 'VLSI for the Information Appliance'
An improved quantum genetic algorithm and its application
RSFDGrC'03 Proceedings of the 9th international conference on Rough sets, fuzzy sets, data mining, and granular computing
Quantum-inspired evolutionary algorithm for a class of combinatorial optimization
IEEE Transactions on Evolutionary Computation
IEEE Transactions on Evolutionary Computation
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Quantum-inspired evolutionary algorithms: a survey and empirical study
Journal of Heuristics
An improved membrane algorithm for solving time-frequency atom decomposition
WMC'09 Proceedings of the 10th international conference on Membrane Computing
A Quantum-Inspired Evolutionary Algorithm Based on P systems for Knapsack Problem
Fundamenta Informaticae
A membrane algorithm with quantum-inspired subalgorithms and its application to image processing
Natural Computing: an international journal
Hi-index | 0.00 |
This paper proposes a real-observation quantum-inspired evolutionary algorithm (RQEA) to solve a class of globally numerical optimization problems with continuous variables. By introducing a real observation and an evolutionary strategy, suitable for real optimization problems, based on the concept of Q-bit phase, RQEA uses a Q-gate to drive the individuals toward better solutions and eventually toward a single state corresponding to a real number varying between 0 and 1. Experimental results show that RQEA is able to find optimal or close-to-optimal solutions, and is more powerful than conventional real-coded genetic algorithm in terms of fitness, convergence and robustness.