Optimal Mobile Crane Repositioning Route Planning Using Particle Swarm Optimization Method

  • Suphawut Malaikrisanachalee Department of Civil Engineering, Faculty of Engineering, Kasetsart University
  • Thanakrit Piyaamornkul Infrastructure Engineering and Management, Department of Civil Engineering, Faculty of Engineering, Kasetsart University
  • Narongrit Wongwai Transportation Engineering and Infrastructure Research Unit, Department of Civil Engineering, Faculty of Engineering at Sriracha, Kasetsart University Sriracha Campus
  • Porjan Tuttipongsawat The Innovation in Infrastructure and Construction Management Research Unit, Department of Civil Engineering, Faculty of Engineering at Sriracha, Kasetsart University Sriracha Campus
Keywords: route planning, mobile crane, particle swarm optimization, metaheuristic algorithm, cost reduction, site simulation, MATLAB, logistics optimization

Abstract

This research aims to develop a repositioning route planning model for mobile cranes using the Particle Swarm Optimization (PSO) algorithm to determine optimal parking positions under real-world site constraints. The objective is to reduce operation time and cost. A simulated case study involving 49 installation points in a warehouse construction project was used. The model was implemented using MATLAB R2024b, with input and result processing managed via Microsoft Excel. The results indicate that the PSO-based model reduced average operation time by 17.4% and crane repositioning frequency by 28.6% compared to Discontinuous Nonlinear Programming (DNLP). The model effectively identified optimal crane positions and demonstrated adaptability to varied numbers of crane and material storage points. Notably, increasing material storage points from 1 to 3 yielded a maximum operation time reduction of 22.9%, confirming PSO’s capability for optimizing construction logistics.

Published
2025-08-21
Issue
2025: The 1st National Conference on Academic Resource, Information Technology and Multidisciplinary 2025
Section
Articles