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• W2116400650 abstract "This paper proposes a new parallel evolutionary algorithm called parallel quantum-inspired genetic algorithm (PQGA). Quantum-inspired genetic algorithm (QGA) is based on the concept and principles of quantum computing such as qubits and superposition of states. Instead of binary, numeric, or symbolic representation, by adopting the qubit chromosome as a representation, QGA can represent a linear superposition of solutions due to its probabilistic representation. QGA is suitable for parallel structures because of rapid convergence and good global search capability. That is, QGA is able to possess the two characteristics of exploration and exploitation simultaneously. The effectiveness and the applicability of PQGA are demonstrated by experimental results on the knapsack problem, which is a well-known combinatorial optimization problem. The results show that PQGA is superior to QGA as well as other conventional genetic algorithms." @default.
• W2116400650 created "2016-06-24" @default.
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• W2116400650 date "2002-11-13" @default.
• W2116400650 modified "2023-10-17" @default.
• W2116400650 title "Parallel quantum-inspired genetic algorithm for combinatorial optimization problem" @default.
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• W2116400650 doi "https://doi.org/10.1109/cec.2001.934358" @default.
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