Proceedings Article10.1109/ICNC.2008.785
Quantum Multi-objective Evolutionary Algorithm with Particle Swarm Optimization Method
Zhiyong Li,Kun Xu,Songbing Liu,Kenli Li +3 more
- 18 Oct 2008
- Vol. 3, pp 672-676
10
TL;DR: The proposed algorithm constructs the new quantum solutions expression for multi-objective optimization particle swarm which adopts the non-dominated sorting method for solutions population and use a new population diversity preserving strategy which is based on the Pareto max-min distance.
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Abstract: This paper proposes a novel algorithm for Multiobjective Optimization Problems based on Quantum Particle Swarm. To improve performance of original particle swarm optimization algorithm and avoid trapping to local excellent situations, this method constructs the new quantum solutions expression for multi-objective optimization particle swarm. It adopts the non-dominated sorting method for solutions population and use a new population diversity preserving strategy which is based on the Pareto max-min distance. The multi dimensional 0-1 knapsack optimization problems are carried out and the results show that the proposed method can efficiently find Pareto optimal solutions that are closer to Pareto font and better on distribution. Especially, this proposed method is outstanding on more complex high-dimensional optimization problems.
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Citations
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TL;DR: A novel Cultural MOQPSO algorithm is proposed, in which cultural evolution mechanism is introduced into quantum-behaved particle swarm optimization to deal with multiobjective problems.
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Multi-population coevolutionary dynamic multi-objective particle swarm optimization algorithm for power control based on improved crowding distance archive management in CRNs
TL;DR: It can be concluded that ICMOPSO algorithm has good abilities of stability, diversity and local search ability, which can provide more throughput optimal allocation schemes for decision makers and ensure the quality of customer service.
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•Journal Article
Multi-objective quantum-behaved particle swarm optimization algorithm based on QPSO and crowding distance sorting
TL;DR: MOQPSO-CD makes full use of QPSO to approximate the true Pareto optimal solutions quickly, and Gaussian mutation operator is introduced to enhance the diversity of solution.
14
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