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Cost Optimization of Projects with Fuzzy Duration Activities Using Genetic Algorithms | ||
| AUT Journal of Civil Engineering | ||
| دوره 8، شماره 1، 2024، صفحه 67-80 اصل مقاله (681.38 K) | ||
| نوع مقاله: Research Article | ||
| شناسه دیجیتال (DOI): 10.22060/ajce.2025.23402.5875 | ||
| نویسندگان | ||
| fateme jazebi* 1؛ moslem bakhshi2 | ||
| 1Department of Civil Engineering, Payame Noor University, Ahwaz, Iran. | ||
| 2Havayar Company, Ahwaz, Iran, Department of Technical office | ||
| چکیده | ||
| The minimum cost is a crucial target of almost all types of construction projects, and it is achieved by efficient scheduling. However, each project is unique and the duration of activities involved in a project often cannot accurately be predicted. In this research, fuzzy sets were the solution. One prominent point of this research was considering the level of risk acceptance, based on which, crisp durations for activities were attained. In other words, fuzzy scheduling was turned into crisp scheduling. Then, a method based on a genetic algorithm was selected to select the operating mode for the smallest project total costs. The last stage of the proposed method was the determination of the fuzzy project cost. Simplifications made in this study make it possible to find optimum solutions in complex problems. Next, an example of a construction project was used which substantiated that a genetic algorithm with its selected input data (population and generation number) and criterion of selecting surviving chromosomes for the next generation (roulette wheel principle) could deliver reliable outcomes and provide a tool for handling real-world construction projects. Furthermore, the performed sensitivity analysis proved that the proposed model is not much sensitive to large variations in the values of the acceptance level of risk. Finally, for to validate of the effectiveness of the proposed model, the case study was solved by three widely-used approaches. This comparison (at least 17% improvement in solutions) was a reason for the fact that the presented model is a tool that helps project managers a lot. | ||
| کلیدواژهها | ||
| Execution Modes؛ Fuzzy Sets؛ Genetic Algorithms؛ Project Scheduling | ||
| مراجع | ||
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[1] F.A. Zammori, M. Braglia, M. Frosolini, A fuzzy multi-criteria approach for critical path definition, International Journal of Project Management, 27(3) (2009) 278-291.
[2] Y. Dorfeshan, B. Vahdani, V. Mohagheghi, S. Mousavi, Solving critical path problem in project network by a new enhanced multi-objective optimization of simple ratio analysis approach with interval type-2 fuzzy sets, International Journal of Engineering, 30(9) (2017) 1352-1361.
[3] D.A. Wood, A critical-path focus for earned duration increases its sensitivity for project-duration monitoring and forecasting in deterministic, fuzzy and stochastic network analysis, Journal of Computational Methods in Sciences and Engineering, 18(2) (2018) 359-386.
[4] S.H. Yakhchali, A path enumeration approach for the analysis of critical activities in fuzzy networks, Information Sciences, 204 (2012) 23-35.
[5] P. Mahdavi-Roshan, S.M. Mousavi, A new interval-valued fuzzy multi-objective approach for project time–cost–quality trade-off problem with activity crashing and overlapping under uncertainty, Kybernetes, 52(10) (2023) 4731-4759.
[6] S. Mandal, J. Maiti, Risk analysis using FMEA: Fuzzy similarity value and possibility theory based approach, Expert Systems with Applications, 41(7) (2014) 3527-3537.
[7] M. Zhao, X. Wang, J. Yu, L. Xue, S. Yang, A construction schedule robustness measure based on improved prospect theory and the Copula-CRITIC method, Applied sciences, 10(6) (2020) 2013.
[8] A.M. Vartouni, L.M. Khanli, A hybrid genetic algorithm and fuzzy set applied to multi-mode resource-constrained project scheduling problem, Journal of Intelligent & Fuzzy Systems, 26(3) (2014) 1103-1112.
[9] A. Sharma, S. Tiwari, Fuzzy Multi-Objective Genetic Algorithm Based Resource Constrained Time-Cost Trade-Off Model under Uncertain Environment, (2021).
[10] N. Dayanand, R. Padman, Project contracts and payment schedules: The client's problem, Management Science, 47(12) (2001) 1654-1667.
[11] Z. He, Y. Xu, Multi-mode project payment scheduling problems with bonus–penalty structure, European Journal of Operational Research, 189(3) (2008) 1191-1207.
[12] S. Sakellaropoulos, A. Chassiakos, Project time–cost analysis under generalised precedence relations, Advances in Engineering Software, 35(10-11) (2004) 715-724.
[13] W. Tabyang, V. Benjaoran, Modified finance-based scheduling model with variable contractor-to-subcontractor payment arrangement, KSCE Journal of Civil Engineering, 20 (2016) 1621-1630.
[14] D.H. Tran, Optimizing time–cost in generalized construction projects using multiple-objective social group optimization and multi-criteria decision-making methods, Engineering, Construction and Architectural Management, 27(9) (2020) 2287-2313.
[15] A. Soltani, T. Fernando, A fuzzy based multi-objective path planning of construction sites, Automation in construction, 13(6) (2004) 717-734.
[16] M.A. Ammar, S.I. Abd-ElKhalek, Criticality measurement in fuzzy project scheduling, International Journal of Construction Management, 22(2) (2022) 252-261.
[17] Y. Yuan, S. Ye, L. Lin, M. Gen, Multi-objective multi-mode resource-constrained project scheduling with fuzzy activity durations in prefabricated building construction, Computers & Industrial Engineering, 158 (2021) 107316.
[18] P.-H. Chen, H. Weng, A two-phase GA model for resource-constrained project scheduling, Automation in Construction, 18(4) (2009) 485-498.
[19] A.A. Najafi, S.T.A. Niaki, M. Shahsavar, A parameter-tuned genetic algorithm for the resource investment problem with discounted cash flows and generalized precedence relations, Computers & Operations Research, 36(11) (2009) 2994-3001.
[20] Y. Huang, X. Zou, L. Zhang, Genetic algorithm–based method for the deadline problem in repetitive construction projects considering soft logic, Journal of Management in Engineering, 32(4) (2016) 04016002.
[21] H. Ke, B. Liu, Fuzzy project scheduling problem and its hybrid intelligent algorithm, Applied Mathematical Modelling, 34(2) (2010) 301-308.
[22] Z. Ma, Z. He, N. Wang, Z. Yang, E. Demeulemeester, A genetic algorithm for the proactive resource-constrained project scheduling problem with activity splitting, IEEE Transactions on Engineering Management, 66(3) (2018) 459-474.
[23] C. Peng, G. Wu, T.W. Liao, H. Wang, Research on multi-agent genetic algorithm based on tabu search for the job shop scheduling problem, PloS one, 14(9) (2019) e0223182.
[24] V.D. Vinayak Pavate, Shreyas Kate, Vaishnavi Satpute, Akshata Patil, Atharva Fasake, A Review-Trade off Time-Cost-Quality by Genetic Algorithm, International Journal for Research in Applied Science & Engineering Technology, 11(6) (2023) 1943-1947
[25] S. Diana, L. Ganapathy, A.K. Pundir, An improved genetic algorithm for resource constrained project scheduling problem, International Journal of Computer Applications, 78(9) (2013).
[26] M.H. Sebt, M.R. Afshar, Y. Alipouri, An Efficient Genetic Agorithm for Solving the Multi-Mode Resource-Constrained Project Scheduling Problem Based on Random Key Representation, International Journal of Supply and Operations Management, 2(3) (2015) 905-924. | ||
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