A framework of quantum-inspired multi-objective evolutionary algorithms and its convergence condition

A general framework of quantum-inspired multi-objective evolutionary algorithms as well as one of its sufficient convergence conditions to Pareto optimal set is proposed.

[1]  Marco Laumanns,et al.  SPEA2: Improving the strength pareto evolutionary algorithm , 2001 .

[2]  Jong-Hwan Kim,et al.  Genetic quantum algorithm and its application to combinatorial optimization problem , 2000, Proceedings of the 2000 Congress on Evolutionary Computation. CEC00 (Cat. No.00TH8512).

[3]  David E. Goldberg,et al.  A niched Pareto genetic algorithm for multiobjective optimization , 1994, Proceedings of the First IEEE Conference on Evolutionary Computation. IEEE World Congress on Computational Intelligence.

[4]  Kalyanmoy Deb,et al.  A fast and elitist multiobjective genetic algorithm: NSGA-II , 2002, IEEE Trans. Evol. Comput..

[5]  G. Rudolph.  Evolutionary Search under Partially Ordered Fitness Sets , 2001 .

[6]  Vlatko Vedral,et al.  Basics of quantum computation , 1998, quant-ph/9802065.

[7]  Jong-Hwan Kim,et al.  Parallel quantum-inspired genetic algorithm for combinatorial optimization problem , 2001, Proceedings of the 2001 Congress on Evolutionary Computation (IEEE Cat. No.01TH8546).

[8]  A. Farhang-Mehr,et al.  Entropy-based multi-objective genetic algorithm for design optimization , 2002 .

[9]  Lothar Thiele,et al.  Multiobjective evolutionary algorithms: a comparative case study and the strength Pareto approach , 1999, IEEE Trans. Evol. Comput..

[10]  David W. Kribs.  A quantum computing primer for operator theorists , 2004 .

[11]  Günter Rudolph,et al.  Convergence properties of some multi-objective evolutionary algorithms , 2000, Proceedings of the 2000 Congress on Evolutionary Computation. CEC00 (Cat. No.00TH8512).

[12]  Thomas Hanne,et al.  A multiobjective evolutionary algorithm for approximating the efficient set , 2007, Eur. J. Oper. Res..

[13]  J. Teich,et al.  The role of /spl epsi/-dominance in multi objective particle swarm optimization methods , 2003, The 2003 Congress on Evolutionary Computation, 2003. CEC '03..

[14]  Carlos A. Coello Coello,et al.  Evolutionary multi-objective optimization: a historical view of the field , 2006, IEEE Comput. Intell. Mag..

[15]  Jong-Hwan Kim,et al.  Quantum-inspired evolutionary algorithm for a class of combinatorial optimization , 2002, IEEE Trans. Evol. Comput..

[16]  Nenzi Wang,et al.  Application of the Genetic Algorithm to the Multi-Objective Optimization of Air Bearings , 2004 .

[17]  Kalyanmoy Deb,et al.  Muiltiobjective Optimization Using Nondominated Sorting in Genetic Algorithms , 1994, Evolutionary Computation.

[18]  Peter W. Shor,et al.  Algorithms for quantum computation: discrete logarithms and factoring , 1994, Proceedings 35th Annual Symposium on Foundations of Computer Science.

[19]  Günter Rudolph,et al.  Evolutionary Search for Minimal Elements in Partially Ordered Finite Sets , 1998, Evolutionary Programming.

[20]  Jong-Hwan Kim,et al.  Quantum-inspired Multiobjective Evolutionary Algorithm for Multiobjective 0/1 Knapsack Problems , 2006, 2006 IEEE International Conference on Evolutionary Computation.

[21]  Mohamed Batouche,et al.  A Quantum Inspired Evolutionary Framework for Multi-objective Optimization , 2005, EPIA.

[22]  Günter Rudolph,et al.  Design and Management of Complex Technical Processes and Systems by Means of Computational Intelligence Methods a Framework of Quantum-inspired Multi-objective Evolutionary Algorithms and Its Convergence Properties a Framework of Quantum-inspired Multi-objective Evolutionary Algorithms and Its Conve , 2022 .

[23]  Peter J. Fleming,et al.  Genetic Algorithms for Multiobjective Optimization: FormulationDiscussion and Generalization , 1993, ICGA.

[24]  Lov K. Grover.  A fast quantum mechanical algorithm for database search , 1996, STOC '96.