Journal of System Simulation
Abstract
Abstract: Aiming at the characteristics of complexity, constraint in discrete manufacturing workshop, in order to minimize the total energy consumption of the workshop as the target, discrete knowledge pigeons algorithm was proposed to solve discrete workshop energy efficiency optimization. In this algorithm, parameter knowledge was introduced into the optimization process to balance local search and global search, and the convergence and optimization ability of the algorithm were improved. The discrete process was added to the pigeons algorithm, which not only preserved the convergence and optimization ability of the algorithm, but also made the algorithm capable of dealing with discrete problems. Through the test of concrete examples, the particle swarm optimization, genetic algorithm and pigeons algorithm results were compared and analyzed, the pigeons algorithm in convergence and optimization ability is superior to the other two algorithms, which verifies the rationality and validity of the algorithm.
Recommended Citation
Xin, Shan; Yan, Wang; and Ji, Zhicheng
(2020)
"Energy Efficiency Optimization for Discrete Workshop Based on Parametric Knowledge Pigeon Swarm Algorithm,"
Journal of System Simulation: Vol. 29:
Iss.
9, Article 36.
DOI: 10.16182/j.issn1004731x.joss.201709036
Available at:
https://dc-china-simulation.researchcommons.org/journal/vol29/iss9/36
First Page
2140
DOI Link
https://doi.org/10.16182/j.issn1004731x.joss.201709036
Last Page
2148
CLC
TP278
Recommended Citation
Shan Xin, Wang Yan, Ji Zhicheng. Energy Efficiency Optimization for Discrete Workshop Based on Parametric Knowledge Pigeon Swarm Algorithm[J]. Journal of System Simulation, 2017, 29(9): 2140-2148.
DOI
10.16182/j.issn1004731x.joss.201709036
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