Construction Site Layout Planning Research Articles

Construction Site Layout Planning: A Social Network Analysis

Construction site layout planning (CSLP) is the strategic arrangement and planning of construction site spaces, which has an enormous impact on the success of any construction project. Over the past two decades, multiple planning models have been developed to generate layouts that maintain safety and productivity within the construction environment. Yet these models vary significantly with disparate assumptions, many of which remain unstated. This study harnesses social network analysis (SNA) as a means to convert data into knowledge. It applies SNA to shed light on CSLP, providing a comprehensive overview of the existing models, and illuminating the critical parameters that should be considered in layout planning. This analysis delves deep into past methodologies and sets the potential for forthcoming research investigations. This study aims to be a reference for readers and researchers venturing into the realm of CSLP. Numerous related records and studies from diverse databases and sources were reviewed and analyzed. Out of these, 70 articles were singled out, from which 14 pivotal parameters were distilled as the foundation for any CSLP framework. Through the application of SNA, gaps within the existing research domain and literature were pinpointed. The study findings demonstrate the growing interest in shifting to cutting-edge approaches in CSLP. However, the results show that the majority of these models in the literature fall short of sufficiently addressing realistic facility representation, noise effects, or the construction impact on the surrounding environment. Accordingly, this research illuminates these knowledge gaps. The findings of this review guide future research by sketching a broad outline for future optimization models and planning studies.

Physics-inspired Metaheuristics for Construction Site Layout Planning Problem

In the construction industry, material handling plays an important role. Finding proper locations for construction facilities not only can affect the expenses, but also it can impact on the process of handling of construction materials. Therefore, in order to supply engineering demands and materials, the construction site layout planning problem (CSLP) within a short-distance transportation is considered as an NP-hard problem. Thus, the researchers are extensively using metaheuristics in order to solve the construction site layout planning problems. This study presents a comparative study of ten physics-inspired metaheuristics with regard to their efficacy in how they can address a real construction site layout problem. In this vein, two case studies are examined in terms of the site layout planning. Finally, the findings reveal that Gravitational Search Algorithm (GSA) and Thermal Exchange Optimization (TEO) have the ability to come up with better solutions, in comparison to other considered optimization algorithms.

Optimization of construction site layout using BIM generative design

Construction site layout planning (CSLP) is the process of allocating temporary facilities needed on construction site. It is a complex process that aims at minimizing travel distances while improving productivity and safety. Although previous studies have enhanced the CSLP, there is a lack of studies that benefit from the potential of Building Information Modelling (BIM)-Generative Design (GD) integration in the field of site layout planning. This study aims to understand the CSLP problem from new aspects to facilitate its use for construction practitioners and site planners. The research presents a new modelling and optimization concept that utilizes BIM-GD tool to target optimum construction site layout plans to ensure a safe and productive work environment. The developed model applies the parametric visual programming basics (VP) to build the layout problem for optimization. The research includes a case study from the literature to demonstrate the applicability of the proposed model. The results show a high validity for the model compared with previous models in terms of defining the problem from new aspects and applying all the calculations within the BIM environment software. The presented study shows great potential from the GD tool for more practical and complex applications in future research.

An Improved Multi-Objective Optimization and Decision-Making Method on Construction Sites Layout of Prefabricated Buildings

Construction site layout planning (CSLP) that considers multi-objective optimization problems is essential to achieving sustainable construction. Previous CSLP optimization methods have applied to traditional cast-in-place buildings, and they lack the application for sustainable prefabricated buildings. Furthermore, commonly used heuristic algorithms still have room for improvement regarding the search range and computational efficiency of optimal solution acquisition. Therefore, this study proposes an improved multi-objective optimization and decision-making method for layout planning on the construction sites of prefabricated buildings (CSPB). Firstly, the construction site and temporary facilities are expressed mathematically. Then, relevant constraints are determined according to the principles of CSLP. Ten factors affecting the layout planning on the CSPB are identified and incorporated into the method of layout planning on the CSPB in different ways. Based on the elitist non-dominated sorting genetic algorithm (NSGA-II), an improved multiple population constraint NSGA-II (MPC-NSGA-II) is proposed. This introduces the multi-population strategy and immigration operator to expand the search range of the algorithm and improve its computational efficiency. Combined with the entropy weight and technique for order preference by similarity to an ideal solution (TOPSIS), improved multi-objective optimization and decision for the CSLP model is developed on the CSPB. Practical cases verify the effectiveness and superiority of the algorithm and model. It is found that the proposed MPC-NSGA-II can solve the drawbacks of the premature and low computational efficiency of NSGA-II for multi-constrained and multi-objective optimization problems. In the layout planning on the CSPB, the MPC-NSGA-II algorithm can improve the quality of the optimal solution and reduce the solution time by 75%.

Construction site layout planning practices in inner-city building projects: space requirement variables, classification and relationship

ABSTRACT An inner-city building construction site for vacant land development or redevelopment of existing property is a site surrounded by buildings, occupants, and busy street(s); its space is the most important but limited resource that needs wisely planned and professionally used. The study aimed to assess the construction site layout planning (CSLP) practice and the classification of space requirement variables for inner-city building sites. Thus, the study adopted a triangulated study approach and the data was collected through a sequential mixed method that includes case studies: semi-structured interviews, document evaluation, and site visits observation followed by a two-round Delphi survey. The study has identified the space requirement variables, classification, and relationship for CSLP of inner-city sites; classified under three categories: Micro-space (four), Macro-space (18), and Paths (five); and have significant to strong associations with each other. The current practice shows the CSLP is overlooked or fragmented which causes a congested site condition. So, the provided insight on the strong relationship between space requirements will be a basis for shifting from the temporary-facility-centered planning methods towards an integrated CSLP approach to overcome contractors’ problems in the continued redevelopment demand of the inner city.

건설현장 배치계획 작성 시스템 개발을 위한 현황 조사 및 핵심기능 도출

To this day, construction site layout planning (CSLP) practice is achieved through a manual approach centered on experience and intuition. Although studies of various approaches have been conducted to solve these problems, it is still difficult to apply them in practice because practitioners may feel counterintuitive and complicated. Therefore, it is necessary to develop a more intuitive and user-friendly CSLP system. As a first step to filling this gap, this study aims to identify the importance of CSLP and its current status in practice, and derive key functions for system development. To do this, literature review, brainstorming, focus group interview, and survey were conducted. As a result, 17 key functions were derived. If the CSLP system is successfully constructed based on the key functions derived from this study, human error can be expected to be improved while the layout planning decisions, and it will help to generate an effective layout solution in terms of productivity and safety.

Simulating travel paths of construction site workers via deep reinforcement learning considering their spatial cognition and wayfinding behavior

Many optimization methods for construction site layout planning (CSLP) generate the shortest path of workers to calculate traveling costs and site safety performance. However, this approach often degrades the solution's reliability because workers in real-life situations do not necessarily take the shortest path to their chosen destination. Thus, this paper proposes a novel approach for generating realistic paths that mimic their wayfinding decision-making process. This approach uses deep reinforcement learning, for which the framework to facilitate its use includes the following elements: (1) the required properties and functions for site objects; and (2) the state, action space, and reward functions intended. The similarity between the paths simulated and the real workers' trajectories has been validated better by 17.8% than the traditional A* algorithm. The proposed approach is expected to be used as an appropriate input, and thereby help improve the reliability of the solutions based on the CSLP optimization methods.

Automated route planning for construction site utilizing Building Information Modeling

Construction Vehicle route planning forms a significant component of Construction Site Layout Planning (SLP). At present, the construction industry has no standard method of planning vehicle routes resulting in chaotic situations on sites. The study proposes an integration of optimization techniques with Building Information Modeling (BIM) to generate feasible routes taking into account the dynamic nature of construction projects. A systematic workflow is developed for the integration of these platforms. The steps involved in the process are presented through a case study highlighting a decision support system for project planners. The advantages of sensitivity analysis alongside a visual interpretation of the construction routing schedule are achieved through the integrated workflow. Thus, the developed workflow provides an approach to enhance the efficiency of daily equipment movements at the site by reducing the possible conflicts and enhancing accessibility. Though the study limits itself in handling the internal vehicular movements, the developed workflow could be extended to manage the project supply chain; moreover, the site personnel movements could be integrated to provide a safer work environment at the construction site.

BIM-based estimation of inputs for site layout planning and locating irregularly shaped facilities

Although construction site layout planning (CSLP) is a significant step in construction planning that has a direct impact on the project performance, its input parameters are mainly obtained by asking site managers and related contractors. The dynamic environment, complexities, and uncertainties of a construction project cause a reduction in the precision of these inputs. This study aims to enhance the CSLP precision by providing a holistic and practical method for estimating these parameters. For this intention, a database is established using the data obtained from the project schedule and BIM to allow the calculation of the input parameters. A new algorithm for facility setup is also proposed for optimizing the facility's shape, which seems beneficial in congested sites where space becomes a limited resource. A case study demonstrates the practicality and functionality of the method. The facility setup algorithm also causes an improvement over restricting facilities to regular shapes.

Multi-objective optimization of dynamic construction site layout using BIM and GIS

Construction site layout planning (CSLP) refers to the facilities' placement in the site boundaries by optimizing layout objectives and considering constraints. This study aims to provide a framework for optimizing the construction site layout dynamically, utilizing information from Building Information Modeling (BIM) and Geospatial Information System (GIS). The framework arranges temporary facilities within the site boundaries by considering a multi-objective optimization problem for minimizing the total on-site travel distance of personnel and equipment between facilities and enhancing the safety level of the construction site. Since a good site layout would increase the safety level of the construction site, facilities are placed based on the proximity relationships among them, which represent the planner preference in locating the facilities near or far from one another due to safety concerns. Then, the Guided Population Archive Whale Optimization Algorithm (GPAWOA) is applied for solving the problem. The contribution of this study includes developing a more realistic model using BIM and GIS together for acquiring the spatial data, navigating dynamically, and considering available indoor and outdoor space continuously. Accordingly, a plugin is developed to find the optimum construction site layout using the ArcGIS APIs and Microsoft C#. Finally, an illustrative case is considered to validate the practicality and functionality of the suggested framework. The results depict that employing the proposed method decreases about 20% of the total on-site traveling distance. Additionally, it results in a safer facilities arrangement regarding the proximity preference, compared with conventional methods.

Dynamic Multi-objective Construction Site Layout Planning Based on BIM

Dynamic Multi-objective Construction Site Layout Planning Based on BIM

Dynamo Visual Programming-Based Generative Design Optimization Model for Construction Site Layout Planning. (Dept. C)

Dynamo Visual Programming-Based Generative Design Optimization Model for Construction Site Layout Planning. (Dept. C)

A BIM-Based Approach to Automated Prefabricated Building Construction Site Layout Planning

A BIM-Based Approach to Automated Prefabricated Building Construction Site Layout Planning

Construction Site Layout Planning Using a Simulation-Based Decision Support Tool

Background: A site layout plan is one of the important decisions to be made in the planning phase of each construction project as it can significantly impact on-site transportation, construction logistics, and safety. This decision could be complicated owing to the uncertainties inherent in construction projects and the complex relationships between the influencing factors and decision variables. Methods: To improve site layout planning, this study aims to develop a simulation-based decision support tool (DST) that enables planners to consider the following: (1) construction uncertainties, (2) construction resources (i.e., material, equipment, and workers), (3) site layout constraints, and (4) mutual impacts between site layout and construction plan variables, for site layout planning of construction projects. Results: The developed DST visualizes the site layout plan within a simulation environment and provides seamless interactions between the site layout model and the simulation model. These capabilities facilitate planning construction site layout using simulation by establishing two-way information flows between the site layout and simulation components, which can further promote application of simulation in construction site layout planning. Usefulness and practicality of the proposed DST is demonstrated in site layout planning of a steel erection project. Conclusions: Using this DST can reduce some common wastes in construction projects and the cost associated with them, including on-site transportation, material handling and storage, and waiting time for the material arrival.

Optimizing travel distance of construction workers considering their behavioral uncertainty using fuzzy graph theory

Travel distance -mostly used in safety and cost objective functions- is the main parameter optimized in construction site layout planning (CSLP) as an optimization problem. While normal CSLP processes assume that every movement at a construction site goes through the particular paths they have assigned, this article presents an innovative method to consider worker behavioral uncertainty (WBU) in whether and how workers follow or deviate from the given paths. In this research, fuzzy graph theory (FGT) helps CSLP consider WBU and shows improved efficiency compared to conventional approaches. The new approach is illustrated in a case study project. The results are affected by WBU in terms of transportation costs and safety risks, but they are still within the range consistent with the literature. Considering WBU through the algorithm presented in this article makes the assumed travel paths more realistic and, thus, CSLP more efficient.

A Typology Model of Temporary Facility Constraints for Automated Construction Site Layout Planning

This study sought to develop a typology model of temporary facility constraints that can be used practically in construction site layout planning (CSLP) automation models. A triangulated methodology (literature review, in-depth interviews, and actual case studies) was used to identify constraints of 11 temporary facilities that are considered mainly in CSLP and to classify them into six constraint types (i.e., dimensional, regional, relocation, non-overlap, inter-facility distance, and visibility constraints) and seven subtypes. In addition, this study proposed computational modeling methods that would allow a computer to judge whether or not the constraints are met by a created construction site layout. This study contributes to CSLP theory by providing a typology model of temporary facilities that can be used in the model-based verification of the created construction site layout and constraint processing condition in CSLP optimization models. This would also help provide efficient, safe, and eco-friendly construction site management, while refraining from experience- and intuition-centered CSLP practices.

Optimization algorithms for construction site layout planning: a systematic literature review

PurposeThis paper aims to analyze and provide insight on the algorithms for the optimization of construction site layout planning (CSLP). It resolves problems, such as the selection of suitable algorithms, considering the optimality, optimization objectives and representation of layout solutions. The approaches for the better utilization of optimization algorithms are also presented.Design/methodology/approachTo achieve the above, existing records (results = 200) were selected from three databases: Web of Science, ScienceDirect and Scopus. By implementing a systematic protocol, the articles related to the optimization algorithms for the CLSP (results = 75) were identified. Moreover, various related themes were collated and analyzed according to a coding structure.FindingsThe results indicate the consistent and increasing interest on the optimization algorithms for the CLSP, revealing that the trend in shifting to smart approaches in the construction industry is significant. Moreover, the interest in metaheuristic algorithms is dominant because 65.3% of the selected articles focus on these algorithms. The optimality, optimization objectives and solution representations are also important in algorithm selection. With the employment of other algorithms, self-developed applications and commercial software, optimization algorithms can be better utilized for solving CSLP problems. The findings also identify the gaps and directions for future research.Research limitations/implicationsThe selection of articles in this review does not consider the industrial perspective and practical applications of commercial software. Further comparative analyses of major algorithms are necessary because this review only focuses on algorithm types.Originality/valueThis paper presents a comprehensive systematic review of articles published in the recent decade. It significantly contributes to the demonstration of the status and selection of CLSP algorithms and the benefit of using these algorithms. It also identifies the research gaps in knowledge and reveals potential improvements for future research.

Modelling the effect of multi-stakeholder interactions on construction site layout planning using agent-based decentralized optimization

Abstract Construction site layout planning (CSLP) is important to ensure that cost, time, quality and environmental impacts are strictly controlled. Even though extensive research has been conducted on CSLP problems, the effect of the multi-stakeholder interactions on optimal site layout plans has been less studied. Therefore, this paper proposes an agent-based decentralized bi-level mathematical model that incorporates decisions from three stakeholders, to examine the CSLP multi-stakeholder interactions. To solve the model, a particle swarm optimization (PSO)-based solution approach is developed to generate the CSLP, construction material logistics planning (CMLP) and security planning (SP) solutions in an integrated CSLP-CMLP/SP system. Specifically, the stakeholders are modelled as individual agents with respective decisions and objective functions, and the inter-dependencies between the layout planner and the other two stakeholders (i.e. the logistics planner and the safety manager) are simultaneously incorporated and dealt with using the bi-level model. The multi-stakeholder interactions are realized by iteratively updating the individual decisions to determine an optimal integrated solution in which the potential stakeholder conflicts in the construction stage are minimized. A case study is given to validate the practicality of the designed model in addressing the CSLP-CMLP and CSLP-SP interactions. The contributions of this research are its applicability to model the effect of multi-stakeholder interactions in agent-based decentralized models, the design of a PSO-based solution approach to achieve an integrated CSLP-CMLP/SP solution, and the provision of academic and practical guidance for decision makers to further enrich global decentralized CSLP research.

A simulated annealing optimization algorithm for equal and un-equal area construction site layout problem

Construction Site Layout Planning (CSLP) is an important problem because of its impact on time, cost, productivity, and safety of the projects. In this paper, CSLP is formulated by the Quadratic Assignment Problem (QAP). At first, two case studies including equal and un-equal area facilities are solved by the simulated annealing optimization algorithm. Then, the obtained results are compared with the other papers. The comparisons show that the proposed Simulated Annealing (SA) is as efficient as ACO, PSO, CBO, ECBO, WOA, WOA-CBO, and ACO-PA which have been proposed by other papers for the same problems. As a result, the comparisons show that SA is as capable as other meta-heuristics of solving the combinatorial optimization problems like CSLP, while the hardware properties and computational times have been compared. Besides the comparisons, the design of experiments shows the relationship between each SA parameter and the computational time of the algorithm. Also, the history of convergence of the proposed SA indicates the high speed of reaching the optimal solution and the artificial intelligence of the proposed SA.

Applying rule-based model-checking to construction site layout planning tasks

Abstract Building Information Modeling (BIM) is a widely established method in the architecture, engineering, construction, and facilities management (AEC/FM) industry. Although BIM focuses on processes throughout the lifecycle of the built environment, the applications in the planning phase, e.g. the generation of construction site layouts, have not reached their full potential yet. One important example herein is the allocation and dimensioning of resources (e.g., building materials and equipment) which is typically carried out by humans according to clearly defined rules and best practices. This paper presents model-based rule checking for the planning of construction site layouts. We demonstrate that existing Business Rule Management Systems (BRMS), such as the open-source rule engine Drools, can be used. We combine Drools with the Industry Foundation Classes (IFC) to retrieve data from a building information model and use the information within the rule engine. We define general model requirements and implement a sample set of prototype rules. We also introduce the concept of offset geometry for rules that, for example, demand a known safety distance between temporary construction site elements. The developed approaches are explained and evaluated in field-realistic, practical case studies. Finally, we present a discussion how the application of the developed rule-based system may assist human decision making in tasks such as safe construction sites layout planning.