Abstract
For the traditional project, three-objective optimization in 3D field (3D imaging technology applications include smart home, autopilot, security monitoring, etc.) can’t meet the actual needs. By two goals safety and environmental factors, balance multi-objective optimization system about the time limit for a project, cost, quality, environment, and safe comprehensive is formed. Using the average rating value adjust dynamically step factor to improve particle swarm optimization (IPSOA), this ensures the diversity of particles and avoids PSO falling into local optimum. Finally, the IPSOA algorithm and PSO algorithms were applied to the multi-objective optimization projects. The results show that IPSOA optimization algorithm is faster and higher precision, and the results of the project in 3D field for solving multi-objective optimization problem are reliable and feasible.
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Acknowledgements
This research was supported by the Jiangsu Planned Projects for Postdoctoral Research Funds No. 1601076B, Xuzhou University of Technology Research Funds No. XKY2018120.
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Zhao, J., Li, S., Li, G. (2020). Research on Multi-objective Optimization Problem of Engineering Project in 3D Field Based on Improved Particle Swarm Optimization Algorithm. In: Kountchev, R., Patnaik, S., Shi, J., Favorskaya, M. (eds) Advances in 3D Image and Graphics Representation, Analysis, Computing and Information Technology. Smart Innovation, Systems and Technologies, vol 179. Springer, Singapore. https://doi.org/10.1007/978-981-15-3863-6_5
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DOI: https://doi.org/10.1007/978-981-15-3863-6_5
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