Meta-heuristic Algorithms for the Tower Crane Planning on the Site
Subject Areas : محاسبات نرم در علوم مهندسی
Roya
Amiri
1
(Department of Civil Engineering, Faculty of Civil and Earth Resources Engineering, Central Tehran Branch, Islamic Azad University, Tehran, Iran)
Javad
Majrouhi Sardroud
2
(Department of Civil Engineering, Faculty of Civil and Earth Resources Engineering, Central Tehran Branch, Islamic Azad University, Tehran, Iran)
Vahid
Momenaei Kermani
3
(Department of Mathematics, Kerman Branch, Islamic Azad University, Kerman, Iran)
Keywords: Metaheuristic Algorithms, Optimization, Site, Tower crane planning,
Abstract :
Research projects show that the desire for intelligent approaches to decision-making at various stages of the construction industry is increasing. Site layout planning is one of the important decision-making processes in the early stages of construction projects, where the location of facilities must be determined within the site. Tower crane is considered as one of the vital and expensive facilities in construction sites. Proper locating of tower crane has a significant impact on the quality, productivity, safety, cost and time of the project. In choosing the location of the tower crane, there are several criteria, including the largest lifting radius and capacity of the tower crane, the type of soil on site, the soil-bearing capacity and the material supply points. Therefore, due to the influence of many factors, tower crane planning is a complex NP-hard optimization problem, which cannot be solved through exact mathematical algorithms as the number of parameters and variables increases. Therefore, it is necessary to define the problem as an optimization problem and integrate it with mathematical modeling to reach the optimal solution. Solving such problems is usually done through metaheuristic algorithms, which belong to the category of approximate algorithms. This study provides a comprehensive review on tower crane planning problem on construction sites using mathematical modeling and metaheuristic algorithms. Based on the findings of this study, research gaps are identified in this field. Therefore, suggestions for future works have been presented in order to solve the shortcomings, which can be the subject of various research articles.
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