Abstract
In high-rise construction projects, inefficient delivery of materials, equipment, and labor can impact the completion time of the project. So, improvement in vertical transportation could save time, facilitate the supply process and reduce costs. The methods introduced for efficiently planning lifts in the construction industry were focused on material transportation and the time of lift activity, which primarily used heuristics and simulations. One of the main challenges that has not been fully addressed in the literature is automatically prioritizing critical activities in the supply process. Other issues include taking into account the night shift and considering the deadline of critical activities. Mixed-Integer Linear Programming (MILP) formulation that integrates both integer and continuous variables can provide an opportunity to obtain an optimal solution. Accordingly, this paper introduces an MILP model that seeks the best allocation of materials and equipment to a given number of lift travel rounds. Also, when the demand exceeds lift capacity, the proposed method allows for efficient prioritization of activities and supplies maximum ordered material with the fewest possible delays. The proposed model, coupled with a novel iterative search algorithm, can achieve the minimum number of travel rounds and the optimum lift planning. Field data from a 22-story construction project is used to test the suggested method. The results demonstrate that the method could effectively minimize delivery times and detect infeasible and undersupplied demands.