Abstract
In this paper, a general framework of quantum-inspired multi-objective evolutionary algorithms is proposed based on the basic principles of quantum computing and general schemes of multi-objective evolutionary algorithms. One of the sufficient convergence conditions to Pareto optimal set is presented and proved under partially order set theory. Moreover, two improved Q-gates are given as examples meeting this convergence condition.
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Li, Z., Li, Z., Rudolph, G. (2007). On the Convergence Properties of Quantum-Inspired Multi-Objective Evolutionary Algorithms. In: Huang, DS., Heutte, L., Loog, M. (eds) Advanced Intelligent Computing Theories and Applications. With Aspects of Contemporary Intelligent Computing Techniques. ICIC 2007. Communications in Computer and Information Science, vol 2. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74282-1_28
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DOI: https://doi.org/10.1007/978-3-540-74282-1_28
Publisher Name: Springer, Berlin, Heidelberg
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