Journal of System Simulation
Abstract
Abstract: To solve the building pipe routing design problem, a mathematical model was formulated. The length of pipe, the number of bends and the laying area were taken as the comprehensive evaluation indexes. Adaptive Simulated Annealing Particle Swarm Optimization (ASAPSO) algorithm was proposed for optimization. In the ASAPSO algorithm, a self-adaptive parameter adjusting strategy and simulated annealing algorithm adjusting the optimal particle location were introduced to enhance the capacity in escaping from the local optimal. A new population initialization method based on the cost of selection probability was designed at the initial population. The simulation showed that compared with the PSO, the ASAPSO can achieve a significant improvement in the quality of the solutions.
Recommended Citation
Wang, Changtao; Sun, Xiaotong; Han, Zhonghua; and Yi, Zhu
(2019)
"A Study of Adaptive Simulated Annealing Particle Swarm Optimization (ASAPSO) Algorithm for Building Pipe Routing Design,"
Journal of System Simulation: Vol. 30:
Iss.
5, Article 41.
DOI: 10.16182/j.issn1004731x.joss.201805041
Available at:
https://dc-china-simulation.researchcommons.org/journal/vol30/iss5/41
First Page
1941
Revised Date
2016-10-21
DOI Link
https://doi.org/10.16182/j.issn1004731x.joss.201805041
Last Page
1949
CLC
TP18
Recommended Citation
Wang Changtao, Sun Xiaotong, Han Zhonghua, Zhu Yi. A Study of Adaptive Simulated Annealing Particle Swarm Optimization (ASAPSO) Algorithm for Building Pipe Routing Design[J]. Journal of System Simulation, 2018, 30(5): 1941-1949.
DOI
10.16182/j.issn1004731x.joss.201805041
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