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Xin Ning - One of the best experts on this subject based on the ideXlab platform.
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Green Performance Evaluation System for Energy-Efficiency-Based Planning for Construction Site Layout
Energies, 2019Co-Authors: Cc Wang, Samad M. E. Sepasgozar, Mudan Wang, Jun Sun, Xin NingAbstract:The location of temporary facilities in a construction project and the entire Site Layout plan directly affect project objectives such as time, labor cost, and material transportation and handling. The Layout of construction Sites also affects entrainment factors such as energy consumption, carbon footprints, and overall construction operation productivity. While Site Layout planning has been intensively investigated from a project objectives perspective, there have been very few studies of energy-efficiency-based planning, or of the sustainability performance of Site Layouts. This study developed a green performance evaluation system aimed at improving the sustainability of construction Site Layouts. The identified factors include six sustainable evaluation categories covering energy conservation and environmental protection, people-oriented principles, construction efficiency, intensity of economic growth, intensity of space use, and the overall control of process. An analytic hierarchy process (AHP) was adopted to determine the weight of each attribute and a fuzzy comprehensive evaluation method was established to carry out the evaluation. The 23 attributes adopted in this paper were identified in the literature; however, the major contribution of this paper is the development of a green performance evaluation system. This system integrates both qualitative and quantitative attributes and provides an overall evaluation of the environmental effectiveness of a construction Site Layout. The proposed evaluation system was validated with a commercial building project. The average utilization ratio of the case study Site was calculated as 94%, and lessons learned are discussed in this paper. The case study analysis identified available Site spaces around the building and examined how the arrangement of resources and facilities ensures effective connection between construction activities. The findings showed that the facility’s Layout plays a crucial role in energy consumption and green performance. The proposed system will support construction project managers to create high-performance construction Site Layouts in more scientific and systematic ways.
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Reducing noise pollution by planning construction Site Layout via a multi-objective optimization model
Journal of Cleaner Production, 2019Co-Authors: Xin Ning, Wenjuan WangAbstract:Abstract Noise pollution from construction activities is a major factor jeopardizing occupational health as well as human living environments. However, previous research mainly focused on reducing noise pollution surrounding sensitive buildings off Site rather than for on-Site workers. Moreover, currently available noise mitigating methods tend to be passive and accompanied by significant additional expenditures. As the location of facilities is a critical factor of noise pollution, this study attempts to analyze how noise pollution for workers can be reduced by optimizing construction Site Layout planning in the pre-construction stage. Considering that mitigating noise by optimizing Site Layout may generate negative impacts on safety and cost, the desired Site Layout should establish a balance among noise reduction, safety improvement and cost control. Therefore, functions addressing potential safety risk and transportation cost arising from interactions between onSite facilities are designed. For solving this multi-objective optimization problem, a hybrid genetic algorithm-ant colony optimization model is applied to obtain trade-off solutions. Feasibility and effectiveness of the optimization model is verified by a case study on a residential building project. This study incorporates noise pollution reduction into Site Layout optimization problems in the pre-construction stage without additional expenditure and in safe manners. It aids future researchers in improving construction sustainability from as early as the planning stage. It also helps Site managers enhance on-Site sustainability incorporating environmental protection, economic efficiency and occupational safety together. The proposed research framework can be used as a reference to balance conflicting sustainability objectives in other industrial Layout facilities as well.
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a quantitative safety risk assessment model for construction Site Layout planning
Safety Science, 2018Co-Authors: Xin Ning, Jingyan Qi, Chunlin WuAbstract:Abstract A good Site Layout is necessary to provide a safe construction Site environment. Previous studies treated construction Site Layout planning as an optimization problem to achieve high safety performance. However, the optimization problem does not contain holistic risk factor analysis. Risk factors such as the dangers of falling objects, noise pollution and hazardous chemicals tend to be neglected. Moreover, when Site managers face different Site Layout scenarios, no safety risk assessment models are currently available to help them make decisions. Therefore, this paper aims to develop a quantitative safety risk assessment model, including factor identification and classification, factor analysis, and assessment function development, to help Site managers evaluate different Site Layout scenarios more accurately and holistically. In factor identification and classification, the interaction flows between facilities are initially considered as risk factors. Safety/environmental concerns which were not deeply probed into by previous studies are also considered. For the above two risk factor categories, safety risk assessment functions are developed according to the likelihood of accident occurrence and the linear attenuation law respectively. Finally, a case study is used to verify the proposed model. This study interprets how to implement Site safety management by means of Site facility Layout improvement. It enriches occupational safety research by providing a systematic model for assessing Site Layout plans in a quantitative and more valid manner. The findings help conduct effective Site safety management by proper facilities displacement during the preconstruction stage and in turn guarantee construction safety in later stages.
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A multi-attribute model for construction Site Layout using intuitionistic fuzzy logic
Automation in Construction, 2016Co-Authors: Xin Ning, Lieyun Ding, Hanbin LuoAbstract: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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cost safety trade off in unequal area construction Site Layout planning
Automation in Construction, 2013Co-Authors: Xin Ning, K C LamAbstract:Abstract Cost and safety are two key elements when designing a good construction Site Layout planning (CSLP). Previous research works always considered CSLP from the aspect of reducing cost and treated SCLP as a single objective optimization problem. In the paper, CSLP was designed by a multi-objective optimization (MOO) model using modified Pareto-based ant colony optimization (ACO) algorithm, which could find a Pareto solution (trade-off Layout) to fulfill the requirement of reducing cost and improve the Site safety level simultaneously. Furthermore, in order to apply MOO model to solve unequal-area problem, the random grids-recognition strategy was employed in the proposed MOO model to solve the unequal-area Site Layout problems without increasing the computational complexities. A case study of a residential building project is used to validate the proposed MOO model and the results are very positive.
Ali Kaveh - One of the best experts on this subject based on the ideXlab platform.
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Multi-objective Optimization of Construction Site Layout
Metaheuristic Optimization Algorithms in Civil Engineering: New Applications, 2020Co-Authors: Ali Kaveh, Armin Dadras EslamlouAbstract:Construction Site Layout planning is one of the managerial aspects of the construction industry and has significant impacts on performance of the Sites. Since in real Site Layout optimization, many objectives are involved, therefore multi-objective algorithms are needed. In this chapter, multi-objective version of two meta-heuristics, CBO and ECBO, are developed and their applicability and performance are checked on a case study. The quality of the obtained results verifies the ability of these algorithms in finding optimal pareto front on this problem. Another tool that is utilized in this chapter is data envelopment analysis (DEA) which by calculating the efficiency of optimal pareto front Layouts, can help decision makers to select the final Layout among the candidates. It should be mentioned that the DEA has previously been used in models with multiple inputs and outputs.
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Construction Site Layout Planning Problem Using Metaheuristic Algorithms: A Comparative Study
Iranian Journal of Science and Technology Transactions of Civil Engineering, 2019Co-Authors: Ali Kaveh, Yasin VaziriniaAbstract:Material handling is one of the essential activities in the construction industry. Suitable location of facilities in the construction Site can affect the costs and duration of the construction material handling process. The construction Site Layout planning to supply material and engineering demands within the minimum transportation distance is a quadratic assignment problem. Metaheuristics are widely used to solve construction Site Layout planning problems. In this article, the performance of four metaheuristic algorithms called charged system search, whale optimization algorithm, vibrating particles system, and enhanced vibrating particles system (EVPS) are compared in terms of their effectiveness in resolving a practical construction Site Layout problem. Results show that EVPS performs better than the other three methods.
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Charged System Search and Magnetic Charged System Search Algorithms for Construction Site Layout Planning Optimization
Periodica Polytechnica Civil Engineering, 2018Co-Authors: Ali Kaveh, Mostafa Khanzadi, Mohammad Rasteghar Moghaddam, Mohammad RezazadehAbstract:Construction Site Layout planning can be considered as an effort to place different temporary facilities in available Site locations such that multiple objectives are satisfied as much as possible. With the extension of high-rise building construction and construction activities besides the lack of available spaces in construction Sites, proper utilization of this resource has been highlighted because of its significant positive influences on direct cost, safety, and security of the Site which consequently affects the total cost and schedule of the project. Thus the construction Site Layout planning is considered as one of the essential and important phases in construction projects. Site Layout planning problem is an NP-Hard problem from the viewpoint of complexity. In this research, two prominent meta-heuristic algorithms, namely Charged System Search (CSS) and Magnetic Charged System Search (MCSS) are utilized to optimize the Site Layout planning problem. The obtained results of implementing these two algorithms for two different types of Site space modeling are compared with the results of the Particle Swarm Optimization (PSO) algorithm and also those of the previous studies. The results illustrate the capability of the CSS and MCSS algorithms in solving the present problem.
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Efficient multi-objective optimization algorithms for construction Site Layout problem
Scientia Iranica, 2017Co-Authors: Ali Kaveh, M. Rastegar Moghaddam, Mostafa KhanzadiAbstract:Construction Site Layout planning is one of the managerial aspects of the construction industry and has significant impacts on performance of the Sites. Since in real Site Layout optimization, many objectives are involved, therefore multi-objective algorithms are needed. In this study, multi-objective version of two meta-heuristics, CBO and ECBO, are developed and their applicability and performance are checked on a case study. The quality of the results obtained, verify the ability of these algorithms in finding optimal pareto front on this problem. Another tool that is utilized in this study is data envelopment analysis (DEA) which by calculating the efficiency of optimal pareto front Layouts, can help decision makers to select the final Layout among the candidates. It should be mentioned that the DEA has previously been used in models with multiple inputs and outputs.
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A hybrid WOA-CBO algorithm for construction Site Layout planning problem
Scientia Iranica, 2017Co-Authors: Ali Kaveh, M. Rastegar MoghaddamAbstract:The whale optimization algorithm (WOA) is a recently developed swarm-based optimization algorithm inspired by the hunting behavior of humpback whales. This study attempts to enhance the original formulation of the WOA by hybridizing it with some concepts of the colliding bodies optimization (CBO) in order to improve solution accuracy, reliability and convergence speed. The new method, called WOA-CBO algorithm, is applied to construction Site Layout planning problem. To show the efficiency and performance of the WOA and WOA-CBO in construction Site Layout problems, three case studies are selected. First case is a discrete and equal area facility Layout problem that every facility could assign to any location. Second case is an unequal area version of discrete facility Layout problem with more constraints and the last case is a continuous model of construction Site Layouts. These cases are studied by WOA, CBO and WOA-CBO, and the results are compared with each other.
K C Lam - One of the best experts on this subject based on the ideXlab platform.
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cost safety trade off in unequal area construction Site Layout planning
Automation in Construction, 2013Co-Authors: Xin Ning, K C LamAbstract:Abstract Cost and safety are two key elements when designing a good construction Site Layout planning (CSLP). Previous research works always considered CSLP from the aspect of reducing cost and treated SCLP as a single objective optimization problem. In the paper, CSLP was designed by a multi-objective optimization (MOO) model using modified Pareto-based ant colony optimization (ACO) algorithm, which could find a Pareto solution (trade-off Layout) to fulfill the requirement of reducing cost and improve the Site safety level simultaneously. Furthermore, in order to apply MOO model to solve unequal-area problem, the random grids-recognition strategy was employed in the proposed MOO model to solve the unequal-area Site Layout problems without increasing the computational complexities. A case study of a residential building project is used to validate the proposed MOO model and the results are very positive.
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Cost–safety trade-off in unequal-area construction Site Layout planning
Automation in Construction, 2013Co-Authors: Xin Ning, K C LamAbstract:Abstract Cost and safety are two key elements when designing a good construction Site Layout planning (CSLP). Previous research works always considered CSLP from the aspect of reducing cost and treated SCLP as a single objective optimization problem. In the paper, CSLP was designed by a multi-objective optimization (MOO) model using modified Pareto-based ant colony optimization (ACO) algorithm, which could find a Pareto solution (trade-off Layout) to fulfill the requirement of reducing cost and improve the Site safety level simultaneously. Furthermore, in order to apply MOO model to solve unequal-area problem, the random grids-recognition strategy was employed in the proposed MOO model to solve the unequal-area Site Layout problems without increasing the computational complexities. A case study of a residential building project is used to validate the proposed MOO model and the results are very positive.
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Conjoining MMAS to ga to solve construction Site Layout planning problem
Journal of Construction Engineering and Management-asce, 2009Co-Authors: K C Lam, Xin Ning, Mike Chun-kit LamAbstract:An optimal construction Site Layout planning (CSLP) is vital for project management. It can reduce the transportation flows and thus the costs of a project. Genetic algorithm (GA) is the most used algorithm to solve Site Layout problems, but randomly generated initial population in GA will decrease solution quality. Max-min ant system (MMAS) can offer a better initial population than the randomly generated initial population at the beginning of GA. In this study, a modified GA (MMAS-GA) formed by conjoining MMAS to the step of initialization of GA is proposed to solve CSLP problems. In order to reveal the computational capability of MMAS-GA to solve CSLP problems, the results of MMAS-GA and traditional GA are compared by solving an equal-area CSLP problem. The results showed that the proposed MMAS-GA algorithm provided a better optimal solution under the objective function of minimizing the transportation flows between the Site facilities. The proposed MMAS-GA algorithm could assist project managers and planners to design optimal construction Site Layout, and thus to reduce construction costs.
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Application of the entropy technique and genetic algorithms to construction Site Layout planning of medium‐size projects
Construction Management and Economics, 2005Co-Authors: K C Lam, C. M. Tang, W. C. LeeAbstract:Genetic algorithms (GAs) have been introduced into Site Layout planning as reported in a number of studies. In these studies, the objective functions were defined so as to employ the GAs in searching for the optimal Site Layout. However, few studies have been carried out to investigate the actual closeness of relationships between Site facilities; it is these relationships that ultimately govern the Site Layout. This study has determined that the underlying factors of Site Layout planning for medium-size projects include work flow, personnel flow, safety and environment, and personal preferences. By finding the weightings on these factors and the corresponding closeness indices between each facility, a closeness relationship has been deduced. Two contemporary mathematical approaches - fuzzy logic theory and an entropy measure - were adopted in finding these results in order to minimize the uncertainty and vagueness of the collected data and improve the quality of the information. GAs were then applied to searching for the optimal Site Layout in a medium-size government project using the GeneHunter software. The objective function involved minimizing the total travel distance. An optimal Layout was obtained within a short time. This reveals that the application of GA to Site Layout planning is highly promising and efficient.
Ahmed W. A. Hammad - One of the best experts on this subject based on the ideXlab platform.
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A multi-objective construction Site Layout planning problem solved through integration of location and traffic assignment models
Construction Management and Economics, 2019Co-Authors: Ahmed W. A. HammadAbstract:Effective construction Site Layout planning is imperative for ensuring the productivity and safety of construction operations during the various phases of a project. Contrary to previous studies where the focus has been merely on the location decisions of operating facilities, this study examines the Site Layout planning problem from the perspective of incorporating planning considerations for on-land traffic assignment on Site. The Site Layout planning problem is thus solved by accounting for location decisions, on-land material handling equipment choices, and traffic assignment on the Site’s ground during construction. A sustainable Site Layout is ensured through minimizing noise pollution measured at noise-sensitive receivers located around the construction Site, minimizing the cost of the Layout adopted, as well as minimizing the total travel time of on-land equipment traversing between the positioned temporary facilities. The problem is initially formulated as a bi-level model and then later reformulated into a single-level model based on a justified relaxation. To handle the multi-objective nature of the resulting problem, the augmented ϵ-constraint approach is utilized to generate the non-dominated Pareto front. Applied to a realistic case, the results of the proposed bi-level model demonstrate that errors of up to 55% in total system travel time can be avoided when traffic assignment on-Site is considered.
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a cutting plane algorithm for the Site Layout planning problem with travel barriers
Computers & Operations Research, 2017Co-Authors: Ahmed W. A. Hammad, Ali AkbarnezhadAbstract:A novel discrete Construction Site Layout planning model (SLP) is proposed, where multiple coverage of locations by facilities is permitted.We contrast the proposed model with the approach commonly adopted in the literature to solve the SLP problem to exact optimality.We quantify the impact of space discretisation on discrete SLP models.We propose a novel cutting plane algorithm to solve large instances of the discrete SLP problem.We provide a comprehensive analysis on the computational effectiveness of the proposed models. Site Layout planning is an imperative procedure that may significantly impact the productivity and the efficiency of logistical operations undertaken on a construction Site. This paper considers the Site Layout planning problem (SLPP) which entails the allocation of temporary facilities on a construction Site in the presence of travel barriers such that the total transportation cost between facilities is minimised. In order to account for travel barriers, the SLPP is typically solved under the assumption that the available region for facility Layout can be discretised. In this paper, we propose a general Mixed Integer Programming (MIP) model to represent the SLPP, accounting for the presence of barriers, and we show how space-discretised formulations can be derived from this model. In particular, we propose a novel MIP model, which permits facilities to cover multiple locations. This is then benchmarked against a commonly adopted MIP model in the literature. We also highlight a systematic procedure to convert the continuous feasible space in SLPP to a set of discretised locations based on the concept of d-visibility, enabling us to approximate the barrier distance function embedded in the objective function. In particular, we focus on presenting a simple space discretisation approach for converting the continuous SLP into a discrete problem for which the discrete SLP models would be applicable. Space-discretised MIP formulations are highly combinatorial and we introduce a cutting plane algorithm to improve their tractability. Specifically, we propose a novel exact location-decomposition algorithm which works from a relaxed MIP formulation and iteratively generates feasibility cuts to converge to an optimal solution. Both space-discretised MIP models and the decomposition algorithm are tested on a large group of instances to analyse their effectiveness in solving the SLPP. Computational results indicate that the proposed location-decomposition algorithm improves on the pure MIP approach and provides a competitive framework to solve realistic SLPP instances.
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A Computational Method for Estimating Travel Frequencies in Site Layout Planning
Journal of Construction Engineering and Management-asce, 2016Co-Authors: Ahmed W. A. Hammad, Ali Akbarnezhad, David Rey, S. Travis WallerAbstract:Optimizing the Layout of facilities on a construction Site to minimize the material handling costs has been widely investigated in the literature. An integral part of the objective function utilized in the previously proposed optimization models is the frequency parameter, which generally provides a rough estimate of the frequency of travel between each pair of facilities at a specific stage of the project. The majority of travel frequencies deduced in prior studies have been estimated merely based on past experience and may not be an actual representation of movements within the project studied. There is currently a lack of a systematic approach for estimating travel frequencies, required in Site Layout planning, based on the information available at early stages of the project. Obtaining a reasonable estimate of the travel frequency matrix requires a realistic evaluation of the material transportation quantities at each construction stage. This necessitates the utilization of information on the progress of different activities and their corresponding material needs during the various stages. This paper presents a framework for obtaining travel frequencies at different construction project phases by taking advantage of the information made available by building information models and project schedules. The estimated frequencies are later embedded as parameters in an optimization model to improve Site Layout planning. The results of a case study are presented to highlight the capabilities of the proposed framework.
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a multi objective mixed integer nonlinear programming model for construction Site Layout planning to minimise noise pollution and transport costs
Automation in Construction, 2016Co-Authors: Ahmed W. A. Hammad, Ali AkbarnezhadAbstract:Abstract The achievement of a sustainable industry in the construction sector requires the consideration of environmental and social impacts of the operations involved, along with the traditionally imperative economic factors affecting the construction project. An implicit social and environmental factor commonly linked with construction is the noise pollution resulting from activities taking placing during the various construction stages. The levels of sound recorded at receivers positioned in the vicinity of the construction Site may be considerably affected by the Site Layout adopted. Site Layout planning with the objective of minimising the construction noise levels has not been investigated in the available literature. To ensure a balance between economic, social and environmental impacts, the planning of the Site should also account for the economic factors associated with the monetary costs of material transportation between facilities, rendering the problem a multi-objective one. This paper presents a novel multi-objective mixed integer nonlinear programming model that minimises noise levels at multiple receivers surrounding the construction Site, as well as on-land material transportation costs, through Site Layout optimisation. An improved transportation cost model accounting for several transportation modes is presented. A Pareto front, listing nondominated global optimum solutions, is obtained for a case study tested using the e-constraint method.
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A Comparison of Mixed Integer Programming Models for the Construction Site Layout Problem
Proceedings of the 32nd International Symposium on Automation and Robotics in Construction and Mining (ISARC 2015), 2015Co-Authors: Ahmed W. A. Hammad, Ali Akbarnezhad, David ReyAbstract:Site Layout planning has been widely investigated in the literature as a means of minimising transportation costs, improving safety etc. The majority of the research conducted focuses on developing adequate formulations capable of producing optimum results. However, there is a lack of consensus on a particular format to implement for the problem, particularly in regards to the assumptions and constraints to be adopted. Distance between facilities, which is an important measure in Site Layout planning, has been modelled in several ways, all in the hope of producing reasonable approximations to the path followed by workers, machinery etc. between facilities. This paper aims to compare the performance of several models of the Site Layout problem. The objective function considered in this study is the transportation cost of material movement between facilities. A main mixed integer programming model is proposed to represent the Site Layout problem and a comparison is carried out against a relaxed variant, where travel distances are approximated. Further, a constraint generation algorithm is presented in a bid to improve the computational performance of the main model.
Thomas W H Ng - One of the best experts on this subject based on the ideXlab platform.
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the application of the ant colony optimization algorithm to the construction Site Layout planning problem
Construction Management and Economics, 2007Co-Authors: Xin Ning, Thomas W H NgAbstract:A good Site Layout is vital to ensure the safety of the working environment, and for effective and efficient operations. Moreover, it minimizes travel distance, decreases materials handling, and avoids the obstruction of materials and plant movement. Based on studies in the manufacturing industry, the cost of materials handling could be reduced by 20-60% if an appropriate facility Layout is adopted. In designing a Site Layout, a planner will first position the key facilities that influence the method and sequence of construction, and then assign the remaining facilities in the available space that is left over. This process is similar to the positioning of facilities in the ant colony optimization (ACO) algorithm. The general principle of the ACO algorithm is to assign facilities to a location one by one, and the occupied locations are deleted from the location scope in the next assignment. In the study, ACO algorithm is employed to resolve the construction Site Layout planning problem in a hypothetical medium-sized construction project. By applying fuzzy reasoning and the entropy technique, the study calculates the closeness relationship between facilities, in which the optimal Site Layout is affected by the mutual interaction of facilities.