Research Article
Application of particle swarm optimization in multi-resource leveling optimization of engineering projects
@INPROCEEDINGS{10.4108/eai.24-2-2023.2330669, author={Jian Tang and Lu Lai}, title={Application of particle swarm optimization in multi-resource leveling optimization of engineering projects}, proceedings={Proceedings of the 2nd International Conference on Engineering Management and Information Science, EMIS 2023, February 24-26, 2023, Chengdu, China}, publisher={EAI}, proceedings_a={EMIS}, year={2023}, month={6}, keywords={particle swarm optimization; relative weights; multiple resources; balanced optimization}, doi={10.4108/eai.24-2-2023.2330669} }- Jian Tang
Lu Lai
Year: 2023
Application of particle swarm optimization in multi-resource leveling optimization of engineering projects
EMIS
EAI
DOI: 10.4108/eai.24-2-2023.2330669
Abstract
The purpose of this study is to use Particle Swarm 0ptimization (PSO) calculation to make the multiple resources in engineering projects reach global equilibrium after calculation. From the single-resource equilibrium optimization theory to the multi-resource optimization problem, the importance of engineering project resources is evaluated, appropriate evaluation indexes are selected, and a multi-resource equilibrium optimization mathematical model is established. Following that, the PSO solves the mathematical model, and the actual start time of activities (i.e., particle position) is constrained and rounded, subject to logical constraints between activities and time constraints. Finally, using the model to solve the case, the obtained results reduce the variance of resource intensity by 89.69% compared to the original solution, and the experimental results show that the PSO can effectively solve this kind of complex problem.