A multi-attribute model for construction site layout using intuitionistic fuzzy logic |
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| Affiliation: | 1. School of Civil Engineering & Mechanics, Huazhong University of Science & Technology, Wuhan, Hubei Province, China;2. School of Investment & Construction Management, Dongbei University of Finance & Economics, Dalian, Liaoning Province, China;3. College of Civil Engineering, Huaqiao University, Xiamen, Fujian Province, China;1. Key Laboratory of Urban and Architectural Heritage Conservation (Southeast University), Ministry of Education, China;1. School of Architecture, Southeast University, 2 Sipailou, Nanjing 210096, China;1. Department of Civil Engineering, Monash University, 23 College Walk, VIC 3800, Australia;2. Department of Civil and Environmental Engineering, University of Michigan, 1221 Beal Avenue, Ann Arbor, MI 48109-2102, United States of America;3. School of Property, Construction and Project Management, RMIT University, 360 Swanston St, Melbourne, VIC 3000, Australia;4. School of Business IT and Logistics, RMIT University, 360 Swanston St, Melbourne, VIC 3000, Australia |
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| Abstract: | Most researchers have concentrated on studying optimization models to produce optimal construction site layout plans using different algorithms, while the overall method for evaluating and selecting the best site layout generated from optimization models has received less attention. In an optimization model, construction cost is generally considered in the objective function. However, several objectives, such as security and tie-in with external transportation, are difficult to quantify in the objective function and were not considered in previous studies. This paper focuses on evaluating and selecting the construction site layout considering qualitative objectives. An intuitionistic fuzzy multi-attribute decision-making model is developed that combines intuitionistic fuzzy set theory and the technique for order preference by similarity to the ideal solution (TOPSIS). This model overcomes the shortcomings of a traditional fuzzy set when describing ambiguous and unclear circumstances by using membership functions. The application of this model for site layout selection is shown to be reasonable and effective based on data from a real construction project. |
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