Lifting Sequence Optimization of Luffing Tower Cranes Considering Motion Paths with Dynamic Programming

Abstract

The lifting sequence of luffing tower cranes is a key factor in the normal operation of construction projects. Accurate estimation of total lifting time is necessary for lifting sequence optimization. Existing formulations for lifting time estimation have two main deficiencies. One is that the relationship between the hoist motion path of the hook and the luffing motion path of the boom is often neglected. The other is that lifting delays resulting from the horizontal motion path of the boom caused by the relative locations of the crane and the lifting start and end points are rarely taken into account. To address those limitations, this paper proposes a lifting sequence optimization model (LSOM) considering motion paths with dynamic programming. The effectiveness of the proposed model is evaluated by comparing it with three conventional lifting strategies [first in–first serve (FIFS), shortest job first (SJF), and nearest neighbor first (NNF)]. The results show that LSOM achieves a shorter total lifting time and higher crane utilization when compared with FIFS, SJF, and NNF.