Affiliation:
1. Hanoi University of Science and Technology
Abstract
Abstract
Quantum Approximate Optimization Algorithm (QAOA) is one of the variational quantum optimizations that is used for solving combinatorial optimization. The QAOA calculates the average of all solutions provided by the quantum circuit. To improve the result, we investigate a new method to combine QAOA and genetic algorithms. The result of QAOA is considered as an initial population method for a genetic algorithm. This approach is applied to solve the max-cut problem, which is very important for quantum computing research. This method is applied to benchmark datasets and the results have been improved significantly.
Publisher
Research Square Platform LLC
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