Formation and Solution of Time Cost Problem with Minimum Human Involvement

Yıl 2021, Cilt: 26 Sayı: 2, 461 - 480, 31.08.2021

Onder Bettemir , Tugay Yücel

https://doi.org/10.17482/uumfd.869234

Cited By: 4

Öz

In this study, solutions that can be implemented by small-scale contractors are searched for the time-cost trade-off problem which aims to create a work schedule with minimum total project cost. A spreadsheet that creates the work schedule in a way that does not require human intervention has been developed and quick data entry and revision opportunity is provided for each activity. Thus, the adverse consequences of unforeseen situations that may arise during the planning and construction stages and repeated calculations for other projects have been reduced. In this study two different scenarios of the time-cost trade-off problems are solved by Genetic Algorithm running on the macro written for the spreadsheet application and the lowest total project cost and construction alternatives are provided. The workload of planning engineers is reduced significantly by creating a schedule that enables the construction to be carried out with the lowest total project cost. It is aimed that the contractors who use the spreadsheet application would maximize their net profits by achieving a significant reduction in cost. Contrary to the project management software used only by construction management professionals, the ease of use of the spreadsheet application and the provided minimum total project cost offer competitive advantage to all actors in the sector.

Anahtar Kelimeler

Genetic Algorithm, Time Cost Trade-Off, Line of Balance, Optimization

ZAMAN MALİYET ÖDÜNLEŞİM PROBLEMİNİN EN AZ İNSAN MÜDAHALESİ İLE OLUŞTURULUP ÇÖZÜLMESİ

Öz

Bu çalışmada, en düşük toplam proje maliyetli iş programı oluşturmayı amaçlayan zaman maliyet ödünleşim problemine küçük ölçekli yüklenicilerin de uygulayabileceği çözüm yöntemleri aranmıştır. İş programını insan müdahalesine ihtiyaç duymayacak şekilde oluşturan bir hesap tablosu geliştirilmiş ve her aktivite için veri girişi ve revizyonların hızlı bir şekilde yapılması sağlanmıştır. Böylece planlama ve inşaat aşamasında ortaya çıkabilecek öngörülmeyen durumların olumsuz etkileri ve başka projeler için tekrarlanan hesaplamalar azaltılmıştır. Bu çalışmada çözülen iki farklı senaryodaki zaman maliyet ödünleşim problemleri için hesap tablosu uygulamasında yazılan makro üzerinde çalıştırılan Genetik Algoritma ile optimizasyon yapılmıştır. En düşük proje maliyet değeri ve yapım alternatifleri kayıt altına alınmıştır. Alternatifler arasındaki en düşük proje maliyeti ile işin gerçekleştirilmesini sağlayan iş programı oluşturulup planlama mühendislerinin iş yükü önemli ölçüde azaltılmıştır. Hesap tablosu uygulamasını kullanacak yüklenicilerin maliyette kayda değer bir iyileşme elde ederek net kârlarını en üst düzeye çıkarmaları amaçlanmıştır. Sadece yapım yönetimi profesyonellerinin kullandığı proje yönetimi yazılımlarının yanı sıra bu çalışmada oluşturulan hesap tablosu uygulaması sağladığı kullanım kolaylığı ve en düşük toplam proje maliyeti ile sektör içerisindeki tüm aktörlere rekabet avantajı sağlamaktadır.

Anahtar Kelimeler

Genetik Algoritma, Zaman Maliyet Ödünleşim Problemi, Doğrusal İş Programı, Optimizasyon

Kaynakça

• Abdel-Basset, M., Ali, M., & Atef, A. (2020). Uncertainty assessments of linear time-cost tradeoffs using neutrosophic set. Computers & Industrial Engineering, 141, 10.1016/j.cie.2020.106286.
• Afruzi, E. N.,Najafi, A. A., Roghanian, E., ve Mazinani, M. (2014). “A multi-objective imperialist competitive algorithm for solving discrete time, cost and quality trade-off problems with mode-identity and resource-constrained situations.” Computers and Operations Research, Vol. 50, pp. 80-96, doi: 10.1016/j.cor.2014.04.003.
• Al-Shihabi, S., ve AlDurgam, M. M. (2020). “The contractor time–cost–credittrade-off problem: integer programming model, heuristic solution, and business insights.” International Transactions in Operational Research, doi:10.1111/itor.12764.
• Albayrak, G. (2020). Novel Hybrid Method in Time–Cost Trade-Offf or Resource-Constrained Construction Projects. Iranian Journal of Science and Technology, Transactions of Civil Engineering, 44(4), 1295-1307, doi.org/10.1007/s40996-020-00437-2.
• Ammar, M. (2011). Optimization of project time-cost trade-off problem with discounted cashflows. Journal of Construction Engineering and Management, 137 (1), pp.65-71, doi: 10.1061/ASCECO.1943-7862.0000256.
• Anagnostopoulos, K. P. ve Kotsikas, L. (2010). “Experimental evaluation of simulated annealing algorithms for the time–cost trade-off problem.” Applied Mathematics and Computation, Vol. 217, No. 1, pp. 260-270, DOI: 10.1016/j.amc.2010.05.056.
• Banihashemi, S. A., ve Khalilzadeh, M. (2020). Time-cost-quality-environmental impact trade-off resource-constrained Project scheduling problem with DEA approach. Engineering, Construction and Architectural Management, doi: 10.1108/ECAM-05-2020-0350.
• Barber, T. J. ve Boardman, J. T. (1988). “Knowledge–based project control employing heuristic optimisation.” IEE Proceedings, Vol. 135, No. 8, pp. 529-538, DOI: 10.1049/ip-a-1.1988.0083.
• Bettemir, (2009), "Optimization of time-cost-resource trade-off problems in project scheduling using meta-heuristic algortithms" Doctoral dissertation, Middle East Technical University.
• Bettemir, Ö. H. (2011). "Experimental design for genetic algorithm simulated annealing for time cost trade-off problems." International Journal of Engineering & Applied Sciences (IJEAS) Vol.3, Issue 1(2011)15-26.
• Bettemir, Ö. H. ve Birgönül, M. T. (2016). " Network Analysis Algorithm for the Solution of Discrete Time-Cost Trade-off Problem." KSCE Journal of Civil Engineering, (2017) 21(4):1047-1058 DOI 10.1007/s12205-016-1615-x.
• Cha, H. S. ve Lee, D. G. (2015). “A case study of time/cost analysis for aged-housing renovation using a pre-made BIM database structure.” KSCE Journal of Civil Engineering, Vol. 19, No. 4, pp. 841-852, doi: 10.1007/s12205-013-0617-1.
• Chen, P. H. ve Weng, H. (2009). "A two-phase GA model for resource-constrained project scheduling." Automation in Construction, 18 (4), pp.485-498, doi: 10.1016/j.autcon.2008.11.003.
• Cheng, M. Y. ve Tran, D. H. (2016). “An efficient hybrid differential evolution based serial method for multimode resource-constrained project scheduling.” KSCE Journal of Civil Engineering, Vol. 20, No. 1, pp. 90-100, doi: 10.1007/s12205-015-0414-0.
• Chiu, Y. S. P. ve Chiu S. W. (2005). “Incorporating expedited time and cost of the end product into the product structure diagram.” International Journal of Machine Tools and Manufacture, Vol. 45, No. 7, pp. 987-991, DOI: 10.1016/j.ijmachtools.2004.10.015.
• Eshtehardian, E., Afshar, A., ve Abbasnia, R. (2009). “Fuzzy-based MOGA approach to stochastic time–cost trade-off problem.” Automation in Construction, Vol. 18, No. 5, pp. 189-198, 2009, doi: 10.1016/j.autcon.2009.02.001.
• Fulkerson, D. R. (1961). “A network flow computation for project cost curves.” Management Science, Vol. 7, No. 2, pp. 167-178, DOI:10.1287/mnsc.7.2.167.
• Geem, Z. W. (2010). “Multiobjective optimization of time-cost trade-off using harmony search.” Journal of Construction Engineering and Management, Vol. 136, No. 6, pp. 711-716, DOI: 10.1061/(ASCE) CO.1943-7862.0000167.
• Hegazy, T. ve Ersahin, T. (2001). Simplified Spreadsheet solutions. II: Overall schedule optimization. Journal of Construction Engineering and Management, 127 (6), pp.469-475, doi: 10.1061/(ASCE)0733-9364(2001)127:6(469).
• Hooshyar B, Rahmani A ve Shenasa M. (2008). "A Genetic algorithm to time cost trade off in project scheduling."IEEE Congress on Evolutionary Computation; 2008.
• Iranmanesh H, Sikandari MR ve Allahverdiloo M. (2008). "Finding pareto optimal front for multi mode time, cost quality trade off in projects cheduling. World Academy of Science, Engineering and Technology 2008; 40, 346-350.
• Jebaseeli, M. E. ve Dhayabaran, D. P. (2015). " An Algorithm to Solve Fully Fuzzy Time Cost Trade off Problems." International Journal of Engineering Science and Innovative Technology (IJESIT), Volume 4, Issue 2, March 2015.
• Kandil A. ve El-Rayes K. (2006). "Parallel genetic algorithms for optimizing resource utilization in large-scale construction projects." Journal of Construction Engineering and Management 2006; 132 (5), 491-498.
• Kang, N., Son, J. ve Lee, S. (2015). "New Time-Cost Trade-Off Model Considering the Sequence of Alternatives Between Activities." Journal of Asian Architecture and Building Engineering /May 2015/ 386.
• Kasaeian A, Reza O ve Afshar A. (2007). "Non dominated archiving genetic algorithm for multi-objective optimization of time-cost trade-off." Proceedings of the 8th WSEAS International Conference on Evolutionary Computing, Vancouver, British Columbia, Canada.
• Ke, H., Maa, W. ve Ni, Y. (2009). "Optimization Models and a GA Based Algorithm for Stochastic Time-Cost Trade Off" Applied Mathematics and Computations 215, 308-313.
• Ke, H. (2014). "Uncertain random time-cost trade-off problem."Journal of Uncertainty Analysis and Applications, 2014, 2:23 http://www.juaa-journal.com/content/2/1/23.
• KelleyJr, J. E. ve Walker, M. R. (1959). “Critical-path planning and scheduling.” InProc. Of eastern joint IRE-AIEE-ACM computer conference Association for Computing Machinery December 1-3,1959, Vol. 1, pp. 160-173.
• Kelley Jr, J. E. (1961). “Critical-path planning and scheduling: Mathematical basis.” Operations Research, Vol. 9, No. 3, pp. 296-320, DOI:10.1287/opre.9.3.296.
• Kim, J.,Kang, C., ve Hwang, I. (2012). “A practical approach to project scheduling: considering the potential quality loss cost in the time–cost trade off problem.” International Journal of Project Management, Vol. 30, No. 2, pp. 264-272, DOI: 10.1016/j.ijproman. 2011.05.004.
• Koo, C., Hong, T., ve Kim, S. (2015). “An integrated multi-objective optimization model for solving the construction time-cost trade-off problem.” Journal of Civil Engineering and Management, Vol. 21, No. 3, pp. 323-333, DOI: 10.3846/13923730.2013.802733.
• Lee, H. S.,Roh, S., Park, M. S., ve Ryu, H. G. (2010). “Optimal option selection for finishing works of high-rise building.” KSCE Journal of Civil Engineering, Vol. 14, No. 5, pp. 639-651.
• Lin, C. L., ve Lai, Y. C. (2020). An improved time-cost trade-off model with optimal labor productivity. Journal of Civil Engineering and Management, 26(2), 113-130.
• Liu, D., Li, H., Wang, H., Qi, C., & Rose, T. (2020). Discrete symbiotic organisms search method for solving large-scale time-cost trade-off problem in construction scheduling. Expert Systems with Applications, 148, 113230.
• Liu, S. S. ve Wang, C. J. (2008). “Resource-constrained construction project scheduling model for profit maximization considering cash flow.” Automation in Construction, Vol. 17, No. 8, pp. 966-974, DOI: 10.1016/j.autcon.2008.04.006.
• Moghadam, E. K.,Sharifi, M., Rafiee, S., ve Chang, Y. K. (2020). Time–Cost–Quality Trade-Off in a Broiler Production Project Using Meta-Heuristic Algorithms: A Case Study. Agriculture, 10(1), 3.
• Monghasemi, S.,Nikoo, M. R., Fasaee, M. A. K., ve Adamowski, J. (2015). “A novel multicriteria decision making model for optimizing time–cost–quality trade-off problems in construction projects.” Expert Systems with Applications, Vol. 42, No. 6, pp. 3089-3104, DOI: 10.1016/j.eswa.2014.11.032.
• Moussourakis, J. ve Haksever, C. (2004). "Flexible Model for time/cost trade off problem." Journal of Construction Engineering and Management, 130 (3), pp.307-314.
• Mungle, S.,Benyoucef, L., Son, Y. J., ve Tiwari, M. K. (2013). “A fuzzy clustering-based genetic algorithm approach for time–cost–quality trade-off problems: A case study of highway construction project.” Engineering Applications of Artificial Intelligence, Vol. 26, No. 8, pp. 1953-1966, DOI: 10.1016/j.engappai.2013.05.006.
• Rahimi M ve Iranmanesh H. (2008) "Multi-objective particle swarm optimization for discrete time cost quality trade-off problems."World Applied Sciences Journal 2008; 4(2), 270-276.
• Rostami, M., Moradinezhad, D., ve Soufipour, A. (2014). “Improved and competitive algorithms for large scale multiple resource constrained project-scheduling problems.” KSCE Journal of Civil Engineering, Vol. 18, No. 5, pp. 1261-1269.
• Sakellaropoulos, S. ve Chassiakos, A.P. (2004). " Project time–cost analysis under generalised precedence relations."Advances in Engineering Software, 35 (2004) 715–724
• Senouci, A. ve El-Rayes, K. (2009). Time-Profit trade-off analysis for construction projects. Journal of Construction Engineering and Management, 135 (8), pp.718-725.
• Tareghian HR ve Taheri SH. A. (2007). "Solution procedure for the discrete time, cost and quality trade off problem using electromagnetic scatter search." Applied Mathematics and Computation 2007; 190 (2), 1136-1145.
• Tavana, M., Abtahi, A. R., ve Khalili-Damghani, K. (2014). “A new multi-objective multi-mode model for solving preemptive time–cost–quality trade-off project scheduling problems.” Expert Systems with Applications, Vol. 41, No. 4, pp. 1830-1846, DOI: 10.1016/j.eswa.2013.08.081.
• Yang, I. T. (2007). “Using elitist particle swarm optimization to facilitate bicriterion time-cost trade-off analysis.” Journal of Construction Engineering and Management, Vol. 133, No. 7, pp. 498-505, DOI:10.1061/(ASCE)0733-9364(2007)133:7(498).
• Yücel, T. (2019). Kesikli zaman maliyet ödünleşim probleminin optimum çözümünün aranması(Yüksek Lisans Tezi). İnönü Üniversitesi, Fen Bilimleri Enstitüsü, Malatya.
• Wang, T., Abdallah, M., Clevenger, C., ve Monghasemi, S. (2019). Time–cost–quality trade-off analysis for planning construction projects. Engineering, Construction and Architectural Management.
• Zandebasiri, M., Vacik, H., Etongo, D., Dorfstetter, Y., Soosani, J., ve Pourhashemi, M. (2019). Application of time-cost trade-off model in forest management projects: The case of Oak decline project. Journal of forest science, 65(12), 481-492.
• Zhang, H. ve Xing, F. (2010). “Fuzzy-multi-objective particle swarm optimization for time–cost–quality trade off in construction.” Automation in Construction, Vol. 19, No. 8, pp. 1067-1075, DOI:10.1016/j.autcon.2010.07.014.
• Zhang, Y. ve Thomas Ng, S. (2012). “An ant colony system based decision support system for construction time-cost optimization." Journal of Civil Engineering and Management, Vol. 18, No. 4, pp.580-589, DOI: 10.3846/13923730.2012.704164.