A New Approach Belonging to EDAs: Quantum-Inspired Genetic Algorithm with Only One Chromosome

• Published in: Advances in Natural Computation pp. 141 - 150
• Main Authors: Zhou, Shude, Sun, Zengqi
• Format: Book Chapter Conference Proceeding
• Language: English
• Published: Berlin, Heidelberg Springer Berlin Heidelberg 2005; Springer
• Series: Lecture Notes in Computer Science
• Subjects: Applied sciences; Artificial intelligence; Classical Electronic Computer; Computer science; control theory; systems; Conventional Genetic Algorithm; Distribution Algorithm; Exact sciences and technology; Genetic Algorithm; Knapsack Problem; Quantum computation; Probabilistic approach; Genetic algorithm; Combinatorial problem; Quantum information; Combinatorial optimization; Mathematical programming
• ISBN: 9783540283201; 354028320X; 3540283234; 9783540283232
• ISSN: 0302-9743; 1611-3349
• DOI: 10.1007/11539902_17

The paper proposed a novel quantum-inspired genetic algorithm with only one chromosome, which we called Single-Chromosome Quantum Genetic algorithm (SCQGA). In SCQGA, by bringing the information representation in quantum computing into the algorithm, only one quantum chromosome (QC) is used to represent all possible states of the entire population. A novel quantum evolution method without using conventional genetic operators such as crossover operator and mutation operator is proposed, in which according to the best individuals generated by QC we adjust the quantum probability amplitude with quantum rotation gates so that the QC can produce more promising individuals with higher probability in the next generation. The paper indicated that SCQGA is a new approach belonging to estimation of distribution algorithms (EDAs). Experiments on solving a class of combinatorial optimization problems show that SCQGA performs better than conventional genetic algorithm.