4.7 Article

Limit-Cycle-Based Mutant Multiobjective Pigeon-Inspired Optimization

Journal

IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION
Volume 24, Issue 5, Pages 948-959

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TEVC.2020.2983311

Keywords

Convergence; Compass; Sociology; Heuristic algorithms; Pareto optimization; Limit-cycle-based mechanism; multiobjective pigeon-inspired optimization (PIO); mutant mechanism; theoretical analysis

Funding

  1. Science and Technology Innovation 2030-Key Project of New Generation Artificial Intelligence [2018AAA0102303, 2018AAA0102403]
  2. National Natural Science Foundation of China [91948204, 61761136008, U1913602, U19B2033, 91648205]
  3. Aeronautical Foundation of China [20185851022]

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This article presents a limit-cycle-based mutant multiobjective pigeon-inspired optimization (PIO). In this algorithm, the limit-cycle-based mechanism is devised to consider the factors that affect the flight of pigeons to simplify the multiobjective PIO algorithm. The mutant mechanism is incorporated to strengthen the exploration capability in the evolutionary process. Additionally, the application of the dual repository makes the nondominated solutions stored and selected to guide the flight of pigeons. Attributed to the limit-cycle-based mutant mechanisms, this algorithm not only obtains the faster convergence speed and higher accuracy but also improves its population diversity. To confirm the universal application of this algorithm, theoretical analysis of the convergence is discussed in this article. Finally, comparative experiments of our proposed algorithm and other five multiobjective methods are conducted to verify the accuracy, efficiency, and convergence stability of the proposed algorithm.

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