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Float-Based Resource Leveling Optimization of Linear Projects
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DOI：10.1109/ACCESS.2020.3027058.png)
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Abstract
En 中文
In recent years, the linear scheduling method (LSM) approach to the linear project scheduling optimization problem has been widely studied by researchers. In this paper, the problem of resource leveling of linear projects under the framework of LSM is studied. Firstly, the concept of a third type of float is proposed, and the advantages of this third type of float to the optimization of linear project resource leveling are analyzed. On this basis, a two-stage optimization process of the linear project resource leveling problem based on the third type of float is proposed. The process takes into account new constraints such as total resource constraint, resource utilization constraint, and construction mileage constraint, and it aims to maximize the space-time flexibility of construction activities and realize the depth optimization of linear project resource leveling. According to the integer nonlinear characteristic of the model, a quantum particle swarm optimization algorithm with a constraint processing mechanism and particle search range restriction is designed. Finally, the effectiveness of the proposed model is verified by case analysis and comparison of the results in previous studies.
Keywords:
Schedules
Optimal scheduling
Acceleration
Heuristic algorithms
Genetic algorithms
Resource management
Linear project
optimal scheduling
project management
quantum particle swarm
resource leveling
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