Work

The application of intelligent optimization algorithms in reducing energy consumption in slipform construction

Year: 2025

Type: article

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.

Source: PLoS ONE

DOI: 10.1371/journal.pone.0336402

Authors: Wenqin Wang, Lijun Li

Institution: Taiyuan University of Technology

Language: English

Topic: Metaheuristic Optimization Algorithms Research

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

SDGs: Affordable and clean energy, Industry, innovation and infrastructure, Responsible consumption and production

Open Access status: gold

Estimated APC paid: $2,382