Multi-objective pigeon-inspired optimization for brushless direct current motor parameter design

Qiu, Huaxin; Duan, Haibin

doi:10.1007/s11431-015-5860-x

Cited by 55 publications

(29 citation statements)

References 29 publications

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“…The entire algorithm shows excellent performance in global optimization and is effective for solving multimodal and non-convex problems with higher dimensions. Multi-objective pigeon-inspired optimization (MPIO) is used for multi-objective optimization in designing the parameters of brushless direct current motors [4]. The multimodal multi-objective pigeon-inspired optimization algorithm (MMPIO) was proposed to figure out the multimodal multi-objective optimization problems [5,6].…”

Section: Introductionmentioning

confidence: 99%

A Compact Pigeon-Inspired Optimization for Maximum Short-Term Generation Mode in Cascade Hydroelectric Power Station

et al. 2020

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Pigeon-inspired optimization (PIO) is a new type of intelligent algorithm. It is proposed that the algorithm simulates the movement of pigeons going home. In this paper, a new pigeon herding algorithm called compact pigeon-inspired optimization (CPIO) is proposed. The challenging task for multiple algorithms is not only combining operations, but also constraining existing devices. The proposed algorithm aims to solve complex scientific and industrial problems with many data packets, including the use of classical optimization problems and the ability to find optimal solutions in many solution spaces with limited hardware resources. A real-valued prototype vector performs probability and statistical calculations, and then generates optimal candidate solutions for CPIO optimization algorithms. The CPIO algorithm was used to evaluate a variety of continuous multi-model functions and the largest model of hydropower short-term generation. The experimental results show that the proposed algorithm is a more effective way to produce competitive results in the case of limited memory devices.

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Section: Introductionmentioning

confidence: 99%

A Compact Pigeon-Inspired Optimization for Maximum Short-Term Generation Mode in Cascade Hydroelectric Power Station

et al. 2020

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“…Furthermore, the PIO is also extended to solve multi-objective problems. Qiu and Duan [19] proposed the multi-objective pigeon inspired optimization (MPIO) to solve the multi-objective optimization problems in designing the parameters of brushless direct current motors. Comparative experimental results with the modified non-dominated sorting genetic algorithm are given to show the feasibility, validity, and superiority of the proposed algorithm.…”

Section: Introductionmentioning

confidence: 99%

A multi-objective pigeon inspired optimization algorithm for fuzzy production scheduling problem considering mould maintenance

Chan

Niu

et al. 2019

Sci. China Inf. Sci.

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The fuzzy production scheduling problem considering mould maintenance (FPSP-MM) is studied. The processing time and the maintenance time are represented by triangular fuzzy numbers. When tasks are executed based on the sequence provided by the fuzzy schedule, the real duration of each task needs to be known so the posteriori solution with deterministic processing times can be obtained. Therefore, the concept of the schedule robustness needs to be considered for the fuzzy problem. The robustness is considered as the optimization objective except for the fuzzy makespan in this research. To optimize these two objective functions, a multi-objective pigeon inspired optimization (MOPIO) algorithm is developed. To extend the pigeon inspired optimization (PIO) algorithm from the single-objective case to the multi-objective case, nondominated solutions are used as candidates for the leader pigeon designation and a special crowding distance is used to ensure a good distribution of solutions in both the objective space and the corresponding decision space. Furthermore, an index-based ring topology is used to manage the convergence speed. Numerical experiments on a variety of simulated scenarios show the excellent efficiency and effectiveness of the proposed MOPIO algorithm by comparing it with other algorithms.

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“…Most problems can be considered as multiobjective optimization problems (MOPs) [1, 2] in the fields of social production [3], engineering design [4], path planning [5], product design [6], motor design [7], mechanics design [8], and so forth. For example, to design a new toll plaza of a highway, at least two objectives should be considered, which are traffic efficiency and land cost.…”

Section: Introductionmentioning

confidence: 99%

AMOBH: Adaptive Multiobjective Black Hole Algorithm

et al. 2017

Computational Intelligence and Neuroscience

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This paper proposes a new multiobjective evolutionary algorithm based on the black hole algorithm with a new individual density assessment (cell density), called “adaptive multiobjective black hole algorithm” (AMOBH). Cell density has the characteristics of low computational complexity and maintains a good balance of convergence and diversity of the Pareto front. The framework of AMOBH can be divided into three steps. Firstly, the Pareto front is mapped to a new objective space called parallel cell coordinate system. Then, to adjust the evolutionary strategies adaptively, Shannon entropy is employed to estimate the evolution status. At last, the cell density is combined with a dominance strength assessment called cell dominance to evaluate the fitness of solutions. Compared with the state-of-the-art methods SPEA-II, PESA-II, NSGA-II, and MOEA/D, experimental results show that AMOBH has a good performance in terms of convergence rate, population diversity, population convergence, subpopulation obtention of different Pareto regions, and time complexity to the latter in most cases.

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Multi-objective pigeon-inspired optimization for brushless direct current motor parameter design

Cited by 55 publications

References 29 publications

A Compact Pigeon-Inspired Optimization for Maximum Short-Term Generation Mode in Cascade Hydroelectric Power Station

A Compact Pigeon-Inspired Optimization for Maximum Short-Term Generation Mode in Cascade Hydroelectric Power Station

A multi-objective pigeon inspired optimization algorithm for fuzzy production scheduling problem considering mould maintenance

AMOBH: Adaptive Multiobjective Black Hole Algorithm

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