VIET NAM NATIONAL UNIVERSITY HO CHI MINH CITY HO CHI MINH CITY UNIVERSITY OF TECHNOLOGY TU ANH NGUYEN DEVELOP A PROJECT PLANNING METHOD BASED ON BUILDING INFORMATION MODEL (BIM) TO OPTIMALLY REDUCE ACTIVITY OVERLAPS AND TIME COST Major: Construction Management Major code: 8580302 MASTER’S THESIS HO CHI MINH CITY, July 2023 THIS THESIS IS COMPLETED AT HO CHI MINH CITY UNIVERSITY OF TECHNOLOGY – VNU-HCM Supervisor: Assoc. Long Duc LUONG Examiner 1: Assoc. Hoc Duc TRAN Examiner 2: Dr. Cuong Viet CHU This master’s thesis is defended at HCM City University of Technology, VNU-HCM on July 13th, 2023.
Master’s Thesis Committee: (Please write down full name and academic rank of each member of the Master’s Thesis Committee) 1. Thu Anh NGUYEN - Chairman 2. Minh Nhat HUYNH - Member, Secretary 3. Hoc Duc TRAN - Reviewer 1 4.
Cuong Viet CHU - Reviewer 2 5. Chau Ngoc DANG - Member Approval of the Chairman of Master’s Thesis Committee and Dean of Faculty of Civil Engineering after the thesis being corrected (If any). CHAIRMAN OF THESIS COMMITTEE HEAD OF FACULTY OF CIVIL ENGINEERING Dr. Thu Anh NGUYEN Assoc.
Tuan Anh LE VIETNAM NATIONAL UNIVERSITY-HO CHI MINH CITY SOCIALIST REPUBLIC OF VIETNAM HO CHI MINH CITY UNIVERSITY OF TECHNOLOGY Independence – Freedom – Happiness THE TASK SHEET OF MASTER’S THESIS Full name: Tu Anh NGUYEN Student code: 2171070 Date of birth: October 16th, 1999 Place of birth: Quang Nam, Vietnam Major: Construction Management Major code: 858032 I. THESIS TOPIC: Develop a project planning method based on building information model (BIM) to optimally reduce activity overlaps and time costs. Phát triển phương pháp hoạch định dự án dựa trên mô hình thông tin BIM để giảm tối ưu sự chồng lấn của các công tác và thời gian – chi phí. TASKS AND CONTENTS: Optimization in Construction Project III.
TASKS STARTING DATE: February 2nd, 2023 IV. TASKS ENDING DATE: June 10th, 2023 V. Long Duc LUONG Ho Chi Minh City, June 10th, 2023 ADVISOR HEAD OF DEPARTMENT Assoc. Long Duc LUONG Dr.
Long Hoai LE DEAN OF FACULTY OF CIVIL ENGINEERING Assoc. Tuan Anh LE i ACKNOWLEDGEMENT I would like to express my deepest appreciation and gratitude to all those who have supported and contributed to the completion of my master thesis in Construction Management as part of the International Master Programs (IMP) at the Ho Chi Minh City University of Technology, Department of Civil Engineering. First and foremost, I would like to extend my heartfelt thanks to my advisor, Assoc. Luong Duc Long.
Your guidance, expertise, and unwavering support throughout the research process have been invaluable. Your profound knowledge and insightful suggestions have helped shape and improve the quality of this thesis. I am truly grateful for your patience, encouragement, and dedication. I would also like to express my sincere gratitude to the faculty members of the Department of Civil Engineering for their continuous encouragement, wisdom, and valuable inputs.
Their commitment to academic excellence and their willingness to share their expertise have greatly enhanced my understanding and knowledge in the field of Construction Management. I would like to extend my appreciation to my fellow classmates and friends who have provided me with valuable insights, discussions, and support throughout my academic journey. Your presence and camaraderie have made this experience enjoyable and memorable. Additionally, I am deeply grateful to the staff and librarians at the Ho Chi Minh City University of Technology for their assistance and resources, which have greatly facilitated my research.
Finally, I would like to acknowledge my family for their unconditional love, encouragement, and understanding throughout my studies. Their unwavering support has been the foundation of my success. Thank you all once again for your guidance, encouragement, and support. Tu Anh NGUYEN ii ABSTRACT With the rise in usage of building information modeling (BIM) systems, there is a greater demand for a construction schedule management system that can make more sophisticated decisions.
When there is a significant overlap between construction activities, it can lead to poorer performance in those areas. As a result, a suitable construction timetable should be created to reduce the overlap of nearby construction operations. One potential solution for this problem is an active system. This research aims to provide a methodical approach and computer system for simulating an ideal construction timetable that eliminates overlapped tasks and improves operational performance.
The primary objectives of this study are to identify overlapping activities, apply fuzzy theory, and evaluate the risks associated with schedule overlap problems. The genetic algorithm (GA) theory is also applied to optimize the overlap of high-risk activities. The study created a four-dimensional (4-D) environment system that utilizes building information modeling (BIM), and it includes a scheduling simulator, as well as fuzzy and GA analysis tools. To demonstrate the effectiveness of this approach, the study presented a case study based on a real project.
Keywords: BIM implementation in construction projects, 4-D modeling, ratio analysis of schedule overlaps, optimization of schedules using genetic algorithm, and time and cost management. iii TÓM TẮT LUẬN VĂN THẠC SĨ Với sự gia tăng trong việc sử dụng các hệ thống mô hình hóa thông tin xây dựng (BIM), nhu cầu về một hệ thống quản lý tiến độ xây dựng có thể đưa ra các quyết định tinh vi hơn ngày càng tăng. Khi có sự chồng chéo đáng kể giữa các hoạt động xây dựng, nó có thể dẫn đến hiệu suất kém hơn trong các lĩnh vực đó. Do đó, cần tạo ra một thời gian biểu xây dựng phù hợp để giảm sự chồng chéo của các hoạt động xây dựng lân cận.
Một giải pháp tiềm năng cho vấn đề này là một hệ thống đang hoạt động. Nghiên cứu này nhằm mục đích cung cấp một cách tiếp cận có phương pháp và hệ thống máy tính để mô phỏng một thời gian biểu xây dựng lý tưởng giúp loại bỏ các nhiệm vụ chồng chéo và cải thiện hiệu suất vận hành. Mục tiêu chính của nghiên cứu này là xác định các hoạt động chồng chéo, áp dụng lý thuyết mờ và đánh giá rủi ro liên quan đến các vấn đề chồng chéo lịch trình. Lý thuyết thuật toán di truyền (GA) cũng được áp dụng để tối ưu hóa sự chồng chéo của các hoạt động rủi ro cao.
Nghiên cứu đã tạo ra một hệ thống môi trường bốn chiều (4- D) sử dụng mô hình hóa thông tin tòa nhà (BIM) và nó bao gồm một trình mô phỏng lập lịch trình, cũng như các công cụ phân tích GA và mờ. Để chứng minh tính hiệu quả của phương pháp này, nghiên cứu đã trình bày một nghiên cứu điển hình dựa trên một dự án thực tế. Từ khóa: Triển khai BIM trong các dự án xây dựng, mô hình 4-D, phân tích tỷ lệ chồng chéo lịch trình, tối ưu hóa lịch trình bằng thuật toán di truyền, quản lý thời gian và chi phí. iv AUTHOR’S COMMITMENT The undersigned below: Student full name: Tu Anh NGUYEN Student ID: 2171070 Place and date of born: Quang Nam Province, Vietnam, October 16th, 1999 Address: Binh Tan District, Ho Chi Minh City With this declaration, the author finishes his master’s thesis entitled “DEVELOP A PROJECT PLANNING METHOD BASED ON BUILDING INFORMATION MODEL (BIM) TO OPTIMALLY REDUCE ACTIVITY OVERLAPS AND TIME COST” under the advisor's supervision.
All works, ideas, and materials that was gain from other references have been cited correctly. Ho Chi Minh City, June 10th, 2023 Tu Anh NGUYEN v TABLE OF CONTENTS TABLE OF CONTENTS. v TABLE OF FIGURES .viii TABLE OF TABLES. x LIST OF ABBREVIATIONS.
xi CHAPTER 1: INTRODUCTION. Object and Range of Study. Scope of the Study. Structure of the Study.
4 CHAPTER 2: LITERATURE REVIEW. Definitions and Concepts. Overlapping time impact. Overlapping costs and benefits.
Overlapping Time-cost tradeoff. Mamdani and Sugeno Fuzzy Inference Systems. BIM implementation in construction planning and scheduling. Optimization in Construction.
Advantages of Genetic Algorithm. 27 CHAPTER 3: RESEARCH METHODOLOGY. Algorithm for Finding Overlapping Schedule in Project Activities. Fuzzy-Based Risk Analysis Algorithm.
Algorithm for Optimizing Schedule Overlapping using Genetic Algorithm. Schedule optimization application process. Function and constraints utilized in the optimization of the project’s schedule. The process of generating an initial solution for the GA algorithms.
Establishing the fitness function. Analysis of Genetic Algorithm operation. Tradeoff between the total cost of risk and the total overlapping duration. System for Optimizing Schedule Overlapping using BIM-Based Simulation.
46 CHAPTER 4: MODEL IMPLEMENTATION AND VALIDATION. Case study 2 – Bloomsdale Residence. 73 CHAPTER 5: CONCLUSION AND RECOMMENDATION. ANNEX A: Case study 2 detail work in MS Project.
ANNEX B: Case study 2 detail project time. ANNEX C: Case study 2 detail risk analysis. ANNEX D: Proposed MATLAB code. 87 viii TABLE OF FIGURES Figure 2.1: Activity on Node (AON) (P.2: Activity on Arrow (AOA) (P.3: Four types of activity relationships (Adopted from (Prasad, 1996)[11]; (Dehghan, Hazini, & Ruwanpura, 2011)[3] .4: The mechanism of activity overlapping (Dehghan & Ruwanpura, 2011)[10] .5: Semi-independent activities' overlapping (Dehghan & Ruwanpura, 2011)[10] .6: Schedule compression comparison .7: Overlapping time impact on the project schedule (Dehghan & Ruwanpura, 2011)[10] .8: Overlapping cost function (Dehghan, Hazini, & Ruwanpura, 2011)[3].9: Fuzzy inference example .10: Direct Cost, Indirect Cost, and Total Cost in Construction (Hegazy, 2002)[19] .11: Optimization in Exact Method (P.12: General structure diagram of Genetic Algorithm .13: The Single Point Crossover Method .14: The Two-Point Crossover Method .15: Uniform Crossover Approach .16: Overall Process of the Model .17: Typical condition of schedule overlapping .18: The process of checking for schedule overlapping for each activity .19: Membership function for Probability (P), Intensity (I), Output and Fuzzy Simulink.20: Fuzzy rule surface in MATLAB .21: A process of schedule optimization using GA to optimize overlapping schedule and time cost .22: TF-based solution generation method utilizing activity relationships .23: Case study 1 bar chart .24: Genetic algorithm with penalty value and average distance in case study 155 Figure 4.25: Optimized project schedule.26: Pareto front time-cost tradeoff for Case study 1 .27: Updated schedule for objective 1 optimization .28: Updated schedule for objective 2 optimization .29: Pareto front of multi-objective optimization .30: Some perspective views of the project .31: Project’s ground floor plan .32: Project's first floor plan .33: Risk degree of activity number 20 and 24, respectively .34: Multi objective optimization in Case study 2 .35: Process of applying GA in MATLAB for achieving Multi-Objective Optimization.
72 x TABLE OF TABLES Table 2.1: Mamdani and Sugeno advantages .3: Determine ES and EF .4: Determine LS and LF .5: Membership function and five Euclidean distance values .6: If-then rules in MATLAB .7: The project activities, description, duration and predecessors of case study 148 Table 4.8: Case study 1-Calculate project schedule .9: Overlapping check for activity '2' .10: Initial SOR value for all activities .12: Initial overlapping duration of all activities .13: Case study 1 updated schedule after optimizing .14: Optimized SOR values for case study 1 .15: New table activity for best solution 1 .16: New table activity for best solution 2 .17: Project's activity, duration, predecessors of case study 2 .18: Top 10 risky activities of the project based on 5 Euclidean distance values66 Table 4.19: Movable duration corresponding with objective 1.20: Movable duration corresponding with objective 2.21: Movable duration exported from MATLAB.22: Comparison of the Optimum Solution from GA and Excel Solver .