การวางแผนเส้นทางการย้ายตำแหน่งของรถเครนแบบเคลื่อนที่ที่เหมาะสมด้วยวิธีการหาคำตอบที่เหมาะสมที่สุดด้วยวิธีฝูงอนุภาค

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.