Construction site layout planning is one of the most important and essential early steps in construction management, which significantly influences project’s productivity. Since the tower crane is one of the key facilities on construction sites, optimized planning
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Construction site layout planning is one of the most important and essential early steps in construction management, which significantly influences project’s productivity. Since the tower crane is one of the key facilities on construction sites, optimized planning and managing its operation can improve construction performance. Determining optimal capacity and location of tower crane are complex combinatorial NP-hard optimization problems that are affected by several interrelated factors. This problem cannot be solved using exact mathematical methods on a large-scale site. Therefore, the use of metaheuristic algorithms is necessary in order to solve it. Tower crane’s location has a significant impact on its required capacity and, as a result, on total cost of material transportation, which was not considered in research for a long time. Recently, in a new research, tower crane’s capacity has been considered as a decision variable in the mathematical model. But the problem has been solved on a small-scale and with a precise method. Since the feasible solution space increases on a real-scale site, therefore, using the precise techniques is not practical to achieve the optimal solution. Therefore, it is necessary to utilize meta-heuristic algorithms to solve the problem. Using Genetic Algorithm, this study presents the optimal type and location of tower crane and material supply point as decision variables based on minimizing the total cost of material transportation on the large-scale site. The results indicate that the GA successfully determines the optimal solution, leading to approximately 14% cost reduction compared with when a site layout is decided based on experience.
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