The application of intelligent optimization algorithms in reducing energy consumption in slipform construction
Wenqin Wang, Lijun Li
TL;DR
This paper introduces a new algorithm that reduces energy use in slipform construction by combining two optimization techniques.
Contribution
A novel Hybrid PSO-Whale Optimization algorithm is proposed for energy-efficient slipform construction.
Findings
The HPWO algorithm reduces energy consumption by an average of 18.5%.
It outperforms traditional optimization methods in energy management.
The algorithm improves interactions between construction systems like hydraulic and vibration.
Abstract
In this work, a new Hybrid PSO-Whale Optimization (HPWO) algorithm is introduced to optimize energy consumption in slipform construction. By combining the global exploration power of Particle Swarm Optimization (PSO) with the local exploitation strengths of Whale Optimization Algorithm (WOA), the HPWO algorithm enhances energy management through dynamic adjustment mechanisms. A comprehensive multi-objective optimization model is developed, addressing the interactions between hydraulic, climbing, and vibration systems. Experimental results demonstrate that the HPWO algorithm reduces energy consumption by an average of 18.5%, outperforming traditional optimization methods and offering a practical solution for improving construction efficiency.
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Taxonomy
TopicsBIM and Construction Integration · Resource-Constrained Project Scheduling · Hydraulic and Pneumatic Systems