Abstract
Construction scheduling is a complex process that features multitudinous sequences of various tasks or activities necessary to accomplish the project within the stipulated duration. Furthermore, determining the parameters influencing construction scheduling, such as the type of construction activities, its duration, dependency relationship, associated probability of occurrence are arduous and uncertain. Hitherto, construction project scheduling predominantly depends on traditional methods, namely Program Evaluation and Review Technique (PERT), Critical Path Method (CPM), Precedence Diagramming Method (PDM) and so on. However, these prevailing scheduling techniques fall short in ascertaining the precarious parameters to establish accurate schedules. Consequently, a more competent approach is required to address the fuzziness and stochastic characteristics of construction schedules. This research proposes integrating Graphical Evaluation and Review Technique (GERT) and Fuzzy Logic (FL) to create Fuzzy-based GERT (F-GERT) for scheduling construction projects. F-GERT utilizes fuzzy operations to handle uncertainty in activity durations. Initial application to a two-storey residential building project demonstrates proximity to the as-built schedule. To reinforce the applicability of F-GERT, it is incorporated for scheduling forty-five real-time construction projects and accuracy is evaluated by comparing it with the actual project duration. The results show the significance of the proposed method in comparison with the existing methods.
Similar content being viewed by others
Abbreviations
- a1, a2, a3, a4 :
-
Quaternary parameters such that 0 ≤ a1 ≤ a2 ≤ a3 ≤ a4
- L n :
-
Number of paths that start from a source node and terminate in the same sink node
- \(\tilde{S}\) :
-
A fuzzy set
- \(\tilde{T}_{ij}\) :
-
Completion time of ith source node, and jth sink node
- T e :
-
Defuzzied completion time of the network
- \(\tilde{T}_{e}\) :
-
Completion time of the network in TFN
- \(\tilde{t}_{i}\) :
-
TFN of ith activity’s duration time
- \(\tilde{t}_{si}\) :
-
TFN of the start time of ith activity’s duration time
- μ(x):
-
Membership function
- p i :
-
Probability of completing the ith activity
- \(p(\tilde{T}_{e}=\tilde{T}_{ij})\) :
-
Arbitrary variable probability function of network completion time
- p si :
-
Probability of the source node
References
Abdi R, Ghasemzadeh HR, Abdollahpour S, Sabzeparvar M, Nasab ADM (2010) Modeling and analysis of mechanization projects of wheat production by GERT Networks. Agricultural Sciences in China 9(7):1078–1083, DOI: https://doi.org/10.1016/S1671-2927(09)60193-0
Ahmad SH (1986) GERT models in an educational institution. International Journal of Systems Science 17(1):187–191, DOI: https://doi.org/10.1080/00207728608926795
Ahuja HN, Dozzi SP, Abourizk SM (1994) Project management techniques in planning and controlling construction projects. Second Ed., John Wiley & Sons, New York
Amer F, Koh HY, Golparvar-Fard M (2021) Automated methods and systems for construction planning and scheduling: Critical review of three decades of research. Journal of Construction Engineering and Management 147(7):03121002, DOI: https://doi.org/10.1061/(ASCE)CO.1943-7862.0002093
Asl ST, Hashemin SS (2018) Completion time of special kind of GERT - Type Networks with Fuzzy Times for Activities. SSRG International Journal of Industrial Engineering 5(1):1–8, DOI: https://doi.org/10.14445/23499362/IJIE-V5I1P101
Atanassov KT (1986) Intuitionistic fuzzy sets. Fuzzy sets and systems 20(1):87–96, DOI: https://doi.org/10.1016/S0165-0114(86)80034-3
Badiru AB (2021) Project management: Systems, Principles, and Applications. Second Ed., CRC Press, Florida, DOI: https://doi.org/10.1201/9780429282829
Baranov VV, Bliznevsky AS, Kaftasyev DA, Tynchenko YA, Kuznetsov AS (2020) “GERT - network optimization model for technologies of hazardous industry management” IOP Conference Series: Materials Science and Engineering Vol. 734, No. 012038, MIST: Aerospace–2019, 18–21 November 2019, Krasnoyarsk, Russia, DOI: https://doi.org/10.1088/1757-899X/734/1/012038
Bellman RE, Zadeh LA (1970) Decision-Making in a Fuzzy Environment. Management Science 17(4):B-141–B-164, DOI: https://doi.org/10.1287/mnsc.17.4.B141
Burt JM, Garman MB (1971) Conditional monte carlo: A simulation technique for stochastic Network Analysis. Management Science 18(3):207–217, DOI: https://doi.org/10.1287/mnsc.18.3.207
Castro-Lacouture D, Süer GA, Gonzalez-Joaqui J, Yates JK (2009) Construction project scheduling with time, Cost, and material restrictions using fuzzy mathematical models and critical path method. Journal of Construction Engineering and Management 135(10):1096–1104, DOI: https://doi.org/10.1061/(ASCE)0733-9364(2009)135:10(1096)
Chen S-M (1996) Evaluating weapon systems using fuzzy arithmetic operations. Fuzzy Sets and Systems 77(3):265–276, DOI: https://doi.org/10.1016/0165-0114(95)00096-8
Chen S-M (1997) A new method for tool steel materials selection under fuzzy environment. Fuzzy Sets Systems 92(3):265–274, DOI: https://doi.org/10.1016/S0165-0114(96)00189-3
Chen S-M (1999) Evaluating the rate of aggregative risk in software development using fuzzy set theory: Cybernetics and Systems. An International Journal 30(1):57–75, DOI: https://doi.org/10.1080/019697299125389
Chen C-T, Huang S-F (2007) Applying fuzzy method for measuring criticality in project network. Information Sciences 177(12):2448–2458, DOI: https://doi.org/10.1016/j.ins.2007.01.035
Cheng C-H (1996) Fuzzy repairable reliability based on fuzzy GERT. Microelectronics Reliability 36(10):1557–1563, DOI: https://doi.org/10.1016/0026-2714(95)00200-6
Cheng C-H (1998) A new approach for ranking fuzzy numbers by distance method. Fuzzy Sets and Systems 95(3):307–317, DOI: https://doi.org/10.1016/S0165-0114(96)00272-2
Clayton MJ (1997) Delphi: A technique to harness expert opinion for critical decision-making tasks in education. Educational Psychology An International Journal of Experimental Educational Psychology 17(4):373–386, DOI: https://doi.org/10.1080/0144341970170401
Coffin MA, Taylor BW (1996) Multiple criteria R & D project selection and scheduling using fuzzy logic. Computers & Operations Research 23(3):207–220, DOI: https://doi.org/10.1016/0305-0548(96)81768-0
Crisp J, Pelletier D, Duffield C, Adams A, Nagy S (1997) The delphi method? Nursing Research 46(2):116–118, DOI: https://doi.org/10.1097/00006199-199703000-00010
Dawson CW, Dawson RJ (1994) Clarification of node representation in generalized activity networks for practical project management. International Journal of Project Management 12(2):81–88, DOI: https://doi.org/10.1016/0263-7863(94)90014-0
De Marco A (2018) Probabilistic scheduling, Project management for facility constructions: A Guide for Engineers and Architects, Springer Cham, 173–185, DOI: https://doi.org/10.1007/978-3-319-75432-1_12
Dorrer M, Dorrer A (2020) Forecasting e-Learning processes using GERT models and process mining tools. Proceeding of the International Scienc eand Technology Conference “FarEastCon 2019,” Solovev, D.B., Savaley, V. V., Bekker, A.T. and Petukhov, V.I. eds., Springer Nature Singapore, 857–866, October 2019, Vladivostok, Russian Federation, Far Eastern Federal University, DOI: https://doi.org/10.1007/978-981-15-2244-4_81
Dorrer MG, Popov AA, Trishkina1 EI, Romanov NA (2020) Building a GERT model of life cycle of educational and scientific information resources using Process Mining technology. Journal of Physics: Conference Series, Vol. 1691, No. 012070, ASEDU-2020: Advances in Science, Engineering and Digital Education, 8–9 October 2020, Krasnoyarsk, Russian Federation, DOI: https://doi.org/10.1088/1742-6596/1691/1/012070
Fedorczak-Cisak M, Kowalska-Koczwara A, Pachla F, Radziszewska-Zielina E, Szewczyk B, Śladowski G, Tatara T (2020) Fuzzy model for selecting a form of use alternative for a historic building to be subjected to adaptive reuse. Energies 13(11), No. 2809, DOI: https://doi.org/10.3390/en13112809
Fedrizzi M (1987) Introduction to fuzzy sets and possibility theory. In: Kacprzyk, J., Orlovski, S.A. (eds) Optimization Models Using Fuzzy Sets and Possibility Theory. Theory and Decision Library, Springer, Dordrecht 4:13–26, DOI: https://doi.org/10.1007/978-94-009-3869-4_2
Gavareshki MHK (2004) New Fuzzy GERT Method for research projects scheduling. 2004 IEEE International Engineering Management Conference (IEEE Cat. No. 04CH37574), 18–21 October 2004, 2:820–824, DOI: https://doi.org/10.1109/IEMC.2004
Geng S, Yang M, Mtici M, Liu S (2023) A resilience assessment framework for complex engineered systems using graphical evaluation and review technique (GERT). Reliability Engineering & System Safety 236:109298, DOI: https://doi.org/10.1016/j.ress.2023.109298
Ghaeli MR, Sadi-Nezhad S (2017) Recent advances on graphical evaluation and review techniques. Journal of Project Management 2(3):107–112, DOI: https://doi.org/10.5267/J.JPM.2017.7.001
Gunduz M, Birgonul MT, Ozdemir M (2016) Fuzzy structural equation model to assess construction site safety performance. Journal of Construction Engineering and Management, No. 4016112, 143(4):1–16, DOI: https://doi.org/10.1061/(ASCE)CO.1943-7862.0001259
Gunduz M, Elsherbeny HA (2020) Critical assessment of construction contract administration using fuzzy structural equation modeling. Engineering, Construction and Architectural Management 27(6):1233–1255, DOI: https://doi.org/10.1108/ECAM-05-2019-0246
Gunduz M, Nielsen Y, Ozdemir M (2015) Fuzzy assessment model to estimate the probability of delay in turkish construction projects. Journal of Management in Engineering 31(4), No. 4014055, DOI: https://doi.org/10.1061/(ASCE)ME.1943-5479.0000261
Hajdu M (1997) Network scheduling techniques for construction project management. Springer, Boston, MA, USA
Hajikarimi A (2011) Introducing an optimized pattern of urban structure via fuzzy GERT networks. International Research Journal of Applied and Basic Sciences 2(11):418–422
Hashemin SS (2010) Fuzzy completion time for alternative stochastic networks. Journal of Industrial Engineering International 6(11):17–22
Helgerson EH (1977) Graphical evaluation and review technique (GERT): A Stochastic Networking Scheme for Systems Acquisition Management, ADA042934, Defense Systems Management Coll Fort Belvoir Va. url: https://apps.dtic.mil/sti/pdfs/ADA042934.pdf (Retrieved in November 2022)
Itakura H, Nishikawa Y (1984) Fuzzy network technique for technological forecasting. Fuzzy Sets and Systems 14(2):99–113, DOI: https://doi.org/10.1016/0165-0114(84)90094-0
Jose KP (2012) GERT Analysis of a three unit cold standby system with single repair facility. Journal of Computer and Mathematical Sciences 3(1):55–62, http://www.compmath-journal.org/dnload/K-P-JOSE/CMJV03I01P0055.pdf (Retrieved November 2022)
Kannan MR (2014) Graphical evaluation and review technique GERT: The Panorama in the Computation and Visualization of Network-Based Project Management. In: Advances in Secure Computing, Internet Services, and Applications, Tripathy, B.K. and Acharjya, D.P. eds., IGI Global, 165–179, DOI: https://doi.org/10.4018/978-1-4666-4940-8.ch009
Kannan MR (2019) Constructability analysis of concrete formwork systems, PhD Dissertation, School of Civil Engineering, Vellore Institute of Technology, Chennai, India
Kayalvizhi S, Gunasekar, Thenmozhi (2016) Evaluation on aggregation risk rate for defuzzification in fuzzy sets. Journal of Computer Science and Engineering 2(11):1–6, https://www.ijrdo.org/index.php/cse/article/view/879/828
Kerzner H (2017) Project management: A Systems Approach to Planning, Scheduling, and Controlling, Twelveth Ed., John Wiley & Sons, New Jersey
Khalilzadeh M, Shakeri H, Gholami H, Amini L (2017) A heuristic algorithm for project scheduling with fuzzy parameters. Procedia Computer Science 121:63–71, DOI: https://doi.org/10.1016/j.procs.2017.11.010
Klenk NL, Hickey GM (2011) A virtual and anonymous, deliberative and analytic participation process for planning and evaluation: The concept mapping policy delphi. International Journal of Forecasting 27(1):152–165, DOI: https://doi.org/10.1016/j.ijforecast.2010.05.002
Klir GJ, Yuan B (2015) Fuzzy sets and fuzzy logic: Theory and Applications, Second Ed., Pearson Education, New Delhi
Kuchta D (2001) Use of fuzzy numbers in project risk (criticality) assessment. International Journal of Project Management 19(5):305–310, DOI: https://doi.org/10.1016/S0263-7863(00)00022-3
Kurihara K, Nishiuchi N (2002) Efficient monte carlo simulation method of GERT-type network for project management. Computers & Industrial Engineering 42(2–4):521–531, DOI: https://doi.org/10.1016/S0360-8352(02)00050-5
Kurihara K, Seki S, Akashi K (1984) An optimization method for investment in a project represented by GERT network. Electrical Engineering in Japan 140C(1):57–64, DOI: https://doi.org/10.1002/eej.4391040119
Kutschenreiter-Praszkiewicz I (2017) Graph theory in product development planning. In: Zawislak, S., Rysinski, J. (Eds) Graph-Based Modelling in Engineering. Mechanisms and Machine Science, Vol. 42, Springer, Cham, 165–173, DOI: https://doi.org/10.1007/978-3-319-39020-8_12
Lachmayer R, Afsari M, Hassani R (2014) C# method for all types of nodes in Fuzzy GERT. International Journal of Artificial Intelligence and Neural Networks 5(1):57–62
Lapunka I, Pisz I, Wittbrodt P (2017) Stochastic scheduling of production orders under uncertainty. International Joint Conference SOCO’17-CISIS’17-ICEUTE’17 León, Spain, 6–8 September, 2017, Proceedings, Pérez Garcia, H., Alfonso-Cendón, J., Sánchez González, L., Quintián, H. and Corchado, E. eds., Advances in Intelligent Systems and Computing, Springer International Publishing, 348–358, DOI: https://doi.org/10.1007/978-3-319-67180-2_34
Li J, Liu X, Lu Y, Wang H (2024) Reliability analysis on energy storage system combining GO-FLOW methodology with GERT network. Reliability Engineering & System Safety 243:109860, DOI: https://doi.org/10.1016/j.ress.2023.109860
Li C-L, Lu L (2017) Research on emergency logistics distribution in complex environment based on GERT. 2017 International Conference on Machine Learning and Cybernetics (ICMLC), 09–12 July 2017, 1–7, DOI: https://doi.org/10.1109/ICMLC.2017.8107734
Li Z, Nie X, Wang B, Fan T (2019) Analysis of the transmission of project duration and cost impacts based on the GERT network technique. Symmetry No. 337, 11(3):1–13, DOI: https://doi.org/10.3390/sym11030337
Liberatore MJ (2002) Project schedule uncertainty analysis using fuzzy logic. Project Management Journal 33(4):15–22, DOI: https://doi.org/10.1177/875697280203300403
Lin K-P, Wen W, Chou C-C, Jen C-H, Hung K-C (2011) Applying fuzzy GERT with approximate fuzzy arithmetic based on the weakest t-norm operations to evaluate repairable reliability. Applied Mathematical Modelling 35(11):5314–5325, DOI: https://doi.org/10.1016/j.apm.2011.04.022
Linstone HA, Turoff MT (1975) The delphi method: Techniques and Applications, Addison-Wesley Reading, MA, https://web.njit.edu/~turoff/pubs/delphibook/delphibook.pdf (Retrieved November 2022)
Liu X, Fang Z, Zhang N (2017) A value transfer GERT network model for carbon fiber industry chain based on input–output table. Cluster Computing 20:2993–3001, DOI: https://doi.org/10.1007/s10586-017-0960-y
Liu S-Y, Liu S-C, Lin J-W (2004) Model formulation and development of fuzzy GERT networks. Journal of the Chinese Institute of Industrial Engineers 21(2):156–166, DOI: https://doi.org/10.1080/10170660409509397
Long LD, Ohsato A (2009) A genetic algorithm-based method for scheduling repetitive construction projects. Automation in Construction 18(4):499–511, DOI: https://doi.org/10.1016/j.autcon.2008.11.005
Lorterapong P, Moselhi O (1996) Project - network analysis using fuzzy sets theory. Journal of Construction Engineering and Management 122(4):308–318, DOI: https://doi.org/10.1061/(ASCE)0733-9364(1996)122:4(308)
Masmoudi M, Haït A (2013) Project scheduling under uncertainty using fuzzy modelling and solving techniques. Engineering Applications of Artificial Intelligence 26(1):135–149, DOI: https://doi.org/10.1016/j.engappai.2012.07.012
Mubarak SA (2019) Other scheduling methods. In Construction Project Scheduling and Control, Fourth Ed., John Wiley & Sons, New Jersey, 329
Mullen PM (2003) Delphi: Myths and Reality. Journal of Health Organization and Management 17(1):37–52, DOI: https://doi.org/10.1108/14777260310469319
Na Z (2011) A new F-GERT network model in consideration of the fuzzy information. International Conference on Management Science and Industrial Engineering (MSIE)-2011, 08–11 January 2011, 1241–1245, DOI: https://doi.org/10.1109/MSIE.2011.5707646
Neumann K (1979) Recent advances in temporal analysis of GERT networks. Zeitschrift für Operations Research 23:153–177, DOI: https://doi.org/10.1007/BF01919481
Nguyen D-T, Le-Hoai L, Basenda Tarigan P, Tran D-H (2022) Tradeoff time cost quality in repetitive construction project using fuzzy logic approach and symbiotic organism search algorithm. Alexandria Engineering Journal 61(2):1499–1518, DOI: https://doi.org/10.1016/j.aej.2021.06.058
Nwadigo OB-K, Naismith N, GhaffarianHoseini A, GhaffarianHoseini A, Tookey J (2021) Construction project planning and scheduling as a dynamic system: A content analysis of the current status, technologies and forward action. Smart and Sustainable Built Environment, Vol. ahead-of-print, No. ahead-of-print, DOI: https://doi.org/10.1108/SASBE-02-2021-0022
Pagnoni A (1990) Planning under precedence/duration constraints: Networking Techniques. In: Project Engineering. Springer, Berlin, Heidelberg, 65–118, DOI: https://doi.org/10.1007/978-3-642-75630-6_5
Pellerin R, Perrier N (2019) A review of methods, techniques and tools for project planning and control. International Journal of Production Research 57(7):2160–2178, DOI: https://doi.org/10.1080/00207543.2018.1524168
Phillips DT, Hogg GL (1976) Stochastic network analysis with resource constraints, Cost Parameters, and Queueing Capabilities Using GERTS Methodologies. Computers & Industrial Engineering 1(1):13–25, DOI: https://doi.org/10.1016/0360-8352(76)90004-8
Prade H (1979) Using fuzzy set theory in a scheduling problem: A case study. Fuzzy Sets and Systems 2(2):153–165, DOI: https://doi.org/10.1016/0165-0114(79)90022-8
Pregina K, Kannan MR (2022) Stochastic project network scheduling technique for construction projects using GERT. In: Loon, L.Y., Subramaniyan, M., Gunasekaran, K. (Eds) Advances in Construction Management. Lecture Notes in Civil Engineering 191:381–392, DOI: https://doi.org/10.1007/978-981-16-5839-6_33
Pritsker AAB (1966) GERT: Graphical evaluation and review technique. The RAND Corporation Santa Monica, CA, https://www.rand.org/content/dam/rand/pubs/research_memoranda/2006/RM4973.pdf (Retrieved November 2022)
Pritsker AAB, Happ WW (1966) GERT: Graphical evaluation and review technique: Part I, Fundamentals. Journal of Industrial Engineering 17(5):267–274
Pritsker AAB, Whitehouse GE (1966) GERT: Graphical evaluation and review technique: Part II, Probabilistic and industrial engineering. Journal of Industrial Engineering 17(6):229–239
Radziszewska-Zielina E, Śladowski G (2017) Proposal of the use of a fuzzy stochastic network for the preliminary evaluation of the feasibility of the process of the adaptation of a historical building to a particular form of use. IOP Conference Series: Materials Science and Engineering 245(7), No. 072029, https://iopscience.iop.org/article/10.1088/1757-899X/245/7/072029/pdf (Retrieved November 2022)
Radziszewska-Zielina E, Śladowski G, Sibielak M (2017) Planning the reconstruction of a historical building by using a fuzzy stochastic network. Automation in Construction 84:242–257, DOI: https://doi.org/10.1016/j.autcon.2017.08.003
Radziszewska-Zielina E, Szewczyk B (2015) Controlling partnering relations in construction operations using fuzzy reasoning. Archives of Civil Engineering 61(3):89–102, DOI: https://doi.org/10.1515/ace-2015-0027
Ramani T, Kannan MR (2014) Scheduling of industrialized construction project using graphical evaluation and review technique GERT. Proceedings of Second International Conference on Advances In Industrial Engineering Applications (ICAIEA2014), Anna University, 6–8 January 2014, 35–39
Reda RM (1990) RPM: Repetitive project modeling. Journal of Construction Engineering and Management 116(2):316–330, DOI: https://doi.org/10.1061/(ASCE)0733-9364(1990)116:2(316)
Ross TJ (2010) Fuzzy logic with engineering applications. Third Ed., John Wiley & Sons
Sackman H (1974) Delphi assessment: Expert Opinion, Forecasting, and Group Process. Santa Monica, Calif.: RAND Corporation, R-1283-PR, 1974, url: https://www.rand.org/pubs/reports/R1283.html (Retrieved in November 2022)
Salkind NJ (Ed.) (2007) Encyclopedia of measurement and statistics. Thousand Oaks, CA: Sage Publications
Semenov S, Liqiang Z, Weiling C, Davydov V (2021) Development a mathematical model for the software security testing first stage. Eastern-European Journal of Enterprise Technologies 3(2):24–34, DOI: https://doi.org/10.15587/1729-4061.2021.233417
Shaheen AA, Fayek AR, AbouRizk SM (2007) Fuzzy numbers in cost range estimating. Journal of Construction Engineering and Management 133(4):325–334, DOI: https://doi.org/10.1061/(ASCE)0733-9364(2007)133:4(325)
Shankar G, Mohapatra BN (1993) GERT Analysis of conditional repetitive group sampling plan. International Journal of Quality & Reliability Management 10(2):50–62, DOI: https://doi.org/10.1108/02656719310027902
Shankar G, Sahani V (1997) GERT Analysis of optimal maintenance float system. OPSEARCH 34:16–26, DOI: https://doi.org/10.1007/BF03398504
Śladowski G, Szewczyk B, Sroka B, Radziszewska-Zielina E (2019) Using stochastic decision networks to assess costs and completion times of refurbishment work in construction. Symmetry 11(3), No. 398, DOI: https://doi.org/10.3390/sym11030398
Tao L, Su X, Javed SA (2022) Time-cost trade-off model in GERT-type network with characteristic function for project management. Computers & Industrial Engineering 169:108222, DOI: https://doi.org/10.1016/j.cie.2022.108222
Watters LJ, Vasilik MV (1971) A stochastic network approach to test and checkout, Santa Monica, Calif.: RAND Corporation, P-4486, 1970, https://www.rand.org/pubs/papers/P4486.html (Retrieved in October 2022)
Whitehouse GE (1970) GERT, A useful technique for analyzing reliability problems. Technometrics 12(1):33–48, DOI: https://doi.org/10.1080/00401706.1970.10488632
Whitehouse GE, Pritsker AAB (1969) GERT: Part III Further statistical results; Counters, renewal times, and correlations. AIIE Transactions 1(1):45–50, DOI: https://doi.org/10.1080/05695556908974412
Wu P, Zhou L, Chen H, Zhou H (2020) An improved fuzzy risk analysis by using a new similarity measure with center of gravity and area of trapezoidal fuzzy numbers. Soft Computin 24(6):3923–3936, DOI: https://doi.org/10.1007/s00500-019-04160-7
Wyrozębski P, Wyrozębska A (2013) Challenges of project planning in the probabilistic approach using PERT, GERT and Monte Carlo: Journal of Management and Marketing 1(1):1–8
Yuan Y, Ye S, Lin L, Gen M (2021) Multi-objective multi-mode resource-constrained project scheduling with fuzzy activity durations in prefabricated building construction. Computers & Industrial Engineering 158(107316), DOI: https://doi.org/10.1016/j.cie.2021.107316
Zadeh LA (1965) Fuzzy sets. Information and Control 8(3):338–353, DOI: https://doi.org/10.1016/S0019-9958(65)90241-X
Zadeh LA (1978) Fuzzy sets as a basis for a theory of possibility. Fuzzy Sets and Systems 1(1):3–28, DOI: https://doi.org/10.1016/0165-0114(78)90029-5
Zhang N, Yan S, Fang Z, Yang B (2021) Fuzzy GERT model based on z-tag and its application in weapon equipment management. Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology 40(6):12503–12519, DOI: https://doi.org/10.3233/JIFS-201731
Zhao J, Xue Z, Li T, Ping J, Peng S (2021) An energy and time prediction model for remanufacturing process using Graphical Evaluation and Review Technique GERT with multivariant uncertainties. Environmental Science and Pollution Research International, Vol. ahead of print, DOI: https://doi.org/10.1007/s11356-021-13438-z
Zhou J, Love PED, Wang X, Teo KL, Irani Z (2013) A review of methods and algorithms for optimizing construction scheduling. Journal of the Operational Research Society 64:1091–1105, DOI: https://doi.org/10.1057/jors.2012.174
Zimmermann HJ (2001) Fuzzy set theory—and its applications. Fourth Ed., Springer Dordrecht, DOI: https://doi.org/10.1007/978-94-010-0646-0
Zou PXW, Zhang G, Wang J (2007) Understanding the key risks in construction projects in China. International Journal of Project Management 25(6):601–614, DOI: https://doi.org/10.1016/j.ijproman.2007.03.001
Acknowledgements
The authors would like to sincerely thank the technical experts and their organizations for their extended support and cooperation in providing valuable information regarding this research work. The contribution of various academicians, construction personnel, contractors, construction workers, and discussants, directly and indirectly during the construction field survey and interpretation are also highly regarded. The authors would like to thank the Editor in Chief, Associate Editors, and all the Reviewers of KSCE Journal for their valuable time, insightful comments and constructive suggestions that greatly contributed to enhancing the quality of this article.
Author information
Authors and Affiliations
Corresponding author
Electronic Supplementary Material
Rights and permissions
About this article
Cite this article
Pregina, K., Kannan, M.R. Fuzzy-Graphical Evaluation and Review Technique for Scheduling Construction Projects. KSCE J Civ Eng (2024). https://doi.org/10.1007/s12205-024-0904-z
Received:
Revised:
Accepted:
Published:
DOI: https://doi.org/10.1007/s12205-024-0904-z