Mathematical programming models for construction site layout problems |
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| Affiliation: | 1. School of Engineering and Advanced Technology, College of Sciences, Massey University, Auckland, New Zealand;2. Department of Building and Real Estate, Faculty of Construction and Environment, The Hong Kong Polytechnic University, Hung Hom, Hong Kong;3. Department of Logistics and Maritime Studies, Faculty of Business, The Hong Kong Polytechnic University, Hung Hom, Hong Kong;1. Business School, Sichuan University, Chengdu 610064, PR China;2. State Key Laboratory of Hydraulics and Mountain River Engineering, Sichuan University, Chengdu 610064, PR China;3. Decision Sciences Department, LeBow College of Business, Drexel University, Philadelphia, PA 19104, USA;1. Department of Management Science and Engineering, School of Economics and Management, Nanjing University of Science and Technology, Nanjing 210094, China;2. Advanced ConsTruction and InfOrmation techNology (ACTION) Laboratory, Department of Civil Engineering and Engineering Mechanics, Columbia University, New York 10027, USA;3. State Key Laboratory of Hydraulics and Mountain River Engineering, Sichuan University, Chengdu 610064, China;1. Université Paris-Est, Institut de Recherche en Constructibilité, ESTP, F-94230 Cachan, France;2. An-Najah National University, Urban Planning Engineering Department, P.O. Box:7, West Bank, Palestine;3. University Paris-Est, Lab. Modélisation et Simulation Multi Echelle (MSME/UMR 8208 CNRS), 5 Bd Descartes, 77454 Marne-La-Vallée, France;4. Laboratoire de Génie Civil et géo-Environnement, Université Lille1, 59 650 Villeneuve d''Ascq, France |
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| Abstract: | We address the construction site layout problem that determines the locations of temporary facilities. Mathematical programming models for the site layout problem are proposed, which can be solved by state-of-the-art solvers to optimality. A number of safety, health and environmental concerns, such as falling objects, dusts, and noise, are incorporated in the extensions of the mathematical models. We demonstrate, using numerical experiments, the superiority of our proposed mathematical programming model over existing heuristics in terms of solution optimality and the wide applicability in terms of handling practical considerations. Based on the results of conducted experiments, the proposed method achieved a 3–19% improvement on optimality over those of the existing heuristics methods. The contribution of this research work includes the advanced development of a mathematical programming model incorporating extended concerns and solving site layout problems within reasonable time. |
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