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Balanced Optimization System of Construction Project Management Based on Improved Particle Swarm Algorithm

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International Conference on Cognitive based Information Processing and Applications (CIPA 2021)

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 84))

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Since the end of the 20th century, the construction industry has developed rapidly. Traditional construction project management involves three control goals: schedule, cost, and quality. With the continuous deepening of the concept of sustainability, the environmental protection goals are the same as the traditional three control goals. It is of great significance to put the multi-objective balanced optimization in the same important position so that the main control objectives of the project can be achieved better. In recent years, swarm intelligence algorithms have been widely introduced into the equilibrium optimization problem of engineering project management, and relatively satisfactory results have been achieved. Particle swarm algorithm is a non-numerical optimization calculation method based on the foraging process of birds and swarm intelligence. Since its proposal, it has received a lot of attention from scholars, and its application research has been solved from purely functional numerical optimization problems. It has penetrated into other fields. In view of this, by improving the level of project management and applying multi-objective optimization technology, my country’s economic development speed can be effectively improved. At present, our country has applied multi-objective optimization to the management of substation engineering projects, and conducted in-depth research on this as the development direction. The average value of Transaction per second is 65.21, which shows that the number of transactions processed by the system per second can well simulate real information query use cases. The average transaction response time is 84.21 s, which is too long. But if the peak response time of 170 s is not considered, the system transaction processing time will eventually stabilize between 30 s, which meets the performance requirements.

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Wang, Y. (2022). Balanced Optimization System of Construction Project Management Based on Improved Particle Swarm Algorithm. In: J. Jansen, B., Liang, H., Ye, J. (eds) International Conference on Cognitive based Information Processing and Applications (CIPA 2021). Lecture Notes on Data Engineering and Communications Technologies, vol 84. Springer, Singapore.

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