EAQGA, a quantum-genetic hybrid that encodes parent-solution bit correlations as CNOT-entangled pairs, reports higher average fitness than classical GA and AQGA on portfolio optimization across simulators and a 100-qubit IBM test.
Hromkovi ˇc, Algorithmics for hard problems: introduction to com- binatorial optimization, randomization, approximation, and heuristics
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.ET 1years
2025 1verdicts
REJECT 1representative citing papers
citing papers explorer
-
EAQGA: A Quantum-Enhanced Genetic Algorithm with Novel Entanglement-Aware Crossovers
EAQGA, a quantum-genetic hybrid that encodes parent-solution bit correlations as CNOT-entangled pairs, reports higher average fitness than classical GA and AQGA on portfolio optimization across simulators and a 100-qubit IBM test.