How many lifts does a construction site need? A Global optimization approach

Purpose Due to the expansion of high-rise construction, construction machinery, especially lifts, has become essential in building projects. Therefore, this paper presents an optimal lift configuration considering the lift’s daily rental, operational, horizontal material handling costs and penalties for material delivery delays for better cost management. Design/methodology/approach The proposed method divides the project into several stages based on the required materials. Then, a novel Mixed-Integer Linear Programming model (MILP) is developed to find the best type, number and location of lifts at every stage. It can accommodate any variation in location, numbers and type of lifts during project execution. The developed model also considers the costs of lift dismantling and installation to avoid additional expenses. Findings The developed mathematical model is tested using field data from a real-world application to demonstrate its ability to minimize project costs and working days. The results indicate that modeling all stages simultaneously while considering installation and dismantling costs reduces project costs by 3.7%. Moreover, including horizontal material movement cost in the objective function has resulted in a 40.8% cost savings, and considering the delay penalties has also reduced the overall project costs by 44.8%. Originality/value This study extends the previous approaches by addressing critical yet underexplored factors, such as the number and location of lifts in a construction site, as well as considering dynamic changes in construction material requirements and delay penalties in a novel mathematical model based on pre-determined timeframes. Unlike most of the similar studies that have focused on simulation tools or heuristic methods to determine the best solution for lift location problems in a construction project, this paper aims to determine a global optimum solution while trying to provide a more practical framework by considering influencing factors that have not been adequately addressed before in the similar studies.