Tekrarlı İnşaat Projesi Çizelgelemesi için Metasezgisel Çok Amaçlı Optimizasyon Yaklaşımı

Yıl 2024, Cilt: 11 Sayı: 24, 438 - 454, 31.12.2024

Gülçağ Albayrak

https://doi.org/10.54365/adyumbd.1477358

Öz

Tekrarlı projeler için çizelgeleme, hem süre hem de maliyet açısından etkili bir proje programı oluşturmada çok önemli bir aşamadır. Bu çalışma, tekrarlı işlemleri bulunan projelere uyarlanmış yenilikçi bir metasezgisel çok amaçlı optimizasyon modeli sunmaktadır. Model, planlayıcılara proje süresini, toplam maliyeti ve kesinti süresini aynı anda en aza indiren optimal çizelgeyi belirleme olanağı veren orijinal özellikleriyle öne çıkmaktadır. Model, Kritik Yol Yöntemi (CPM) planlama yeteneklerini korurken, öğrenme ve unutma etkileri, etkinlikler arası yumuşak mantık, iş kesintileri, birden fazla ekip oluşumu, her faaliyet için birden fazla inşaat yöntem seçimi dahil olmak üzere çeşitli kısıtlamaları ve faktörleri kapsamaktadır. Bu yaklaşımın etkinliği, tekrarlı projeler için proje süresini, maliyetini ve kesintiyi en aza indirerek daha yüksek doğrulukla en uygun programları sunma yeteneğini gösteren iki örnek olay incelemesine uygulanarak doğrulanmaktadır. Ayrıca, öğrenme etkilerinin, yazılım mantığının ve iş kesintisi ödeneklerinin optimizasyon sürecine entegrasyonu, proje süresini ve maliyetini önemli ölçüde azaltmakta ve böylece daha kesin ve güvenilir optimum çözümler elde edilmektedir.

Anahtar Kelimeler

Öğrenme etkisi, optimizasyon, proje planlama, tekrarlı proje, yumuşak mantık

Metaheuristic Multi-Objective Optimization Approach for Repetitive Construction Project Scheduling

Öz

The optimization of schedules for repetitive projects is a crucial phase in establishing an effective project timeline concerning both duration and cost. This study presents an innovative metaheuristic multi-objective optimization model tailored for repetitive projects. Distinguished by its original features, this model empowers schedulers to identify an optimal schedule that concurrently minimizes project duration, total cost, and interruption time. It encompasses various constraints and factors, including learning and forgetting effects, inter-activity soft logic, limited work interruption allowances, multiple crew formations, multiple construction methods per activity, while retaining all Critical Path Method (CPM) scheduling capabilities. The effectiveness of this new approach was validated through application to two case studies, demonstrating its capability to deliver optimal schedules for repetitive projects with heightened accuracy in minimizing project duration, cost, and interruption. Furthermore, the integration of learning effects, soft logic, and work interruption allowances within the optimization process substantially reduced project duration and cost, thereby yielding more precise and dependable optimal solutions.

Anahtar Kelimeler

Learning effect, optimization, project planning, repetitive projets, soft logic

Kaynakça

• Monghasemi S, Abdallah M. Linear optimization model to minimize total cost of repetitive construction projects and identify order of units. Journal of Management in Engineering ASCE 2021; 37(4).
• Zou X, Zhang L. A constraint programming approach for scheduling repetitive projects with atypical activities considering soft logic. Automation in Construction 2020; 109.
• Arditi D, Tokdemir O, Suh K. Challenges in line-of-balance scheduling. Journal of Construction Engineering and Management 2002; 128(6): 545-556.
• Johnston DW. Linear scheduling method for highway construction. Journal of the Construction Division ASCE 1981; 107(2): 247-261.
• Arditi D, Albulak M. Line-of-balance scheduling in pavement construction. Journal of Construction Engineering and Management ASCE 1986; 112(3): 411-424.
• Okudan O, Çevikbaş M, Işık Z. An exploratory study on the critical features of construction project planning software. Sigma Journal of Engineering and Natural Sciences 2023; 41(4): 781-792.
• Zhang L, Zou X. Chapter 6 - Resource-constrained scheduling in repetitive construction projects. Repetitive Project Scheduling: Theory and Methods, Elsevier 2015; 71-85.
• Zou X, Zhang L, Zhang Q. A biobjective optimization model for deadline satisfaction in line-of- balance scheduling with work interruptions consideration. Mathematical Problems in Engineering 2018; Article ID 6534021.
• Fan S, Sun K, Wang Y. GA optimization model for repetitive projects with soft logic. Automation in Construction 2012; 21: 253-261.
• Tamimi S, Diekmann J. Soft logic in network analysis. Journal of Computing in Civil Engineering 1988; 2(3): 289-300.
• Huang R, Sun K. A GA optimization model for workgroup-based repetitive scheduling (WoRSM). Advances in Engineering Software 2009; 40:3, 212-228.
• Moselhi O, Hassanein A. Optimized scheduling of linear projects. Journal of Construction Engineering and Management ASCE 2003; 129(6): 664-673.
• García‐Nieves JD, Ponz‐Tienda JL, Ospina‐Alvarado A, Bonilla‐Palacios M. Multipurpose linear programming optimization model for repetitive activities scheduling in construction project. Automation in Construction 2019; 105.
• Altuwaim A, El-Rayes K. Optimizing the scheduling of repetitive construction to minimize interruption cost. Journal of Construction Engineering and Management 2018; 144(7).
• Heravi G, Moridi S. Resource-constrained time-cost tradeoff for repetitive construction projects. KSCE Journal of Civil Engineering 2019; 23(8): 3265-3274.
• Bakry I. Optimized scheduling of repetitive construction projects under uncertainty. PhD thesis, Department of Building, Civil and Environmental Engineering, Concordia University, Montreal 2014.
• Reda R. RPM repetitive project modelling. Journal of Construction Engineering and Management ASCE 1990; 116(2): 316-330.
• Moselhi O, El-Rayes K. Scheduling of repetitive projects with cost optimization. Journal of Construction Engineering and Management ASCE 1993; 119(4): 681-697.
• Senouci A, Eldin N. Dynamic programming approach to scheduling of nonserial linear project. Journal of Computing in Civil Engineering 1996; 10(2): 106-114.
• Hegazy T, Wassef N. Cost optimization in projects with repetitive nonserial activities. Journal of Construction Engineering and Management ASCE 2001; 127(3): 183-191.
• Elbeltagi E, Elkassas E, Abdel Rasheed I, Al-Tawil S. Scheduling and cost optimization of repetitive projects using genetic algorithms. ICCTA Alexandria Egypt 2007.
• El-Rayes K, Moselhi O. Optimizing resource utilization for repetitive construction projects. Journal of Construction Engineering and Management ASCE 2001; 127(1): 18-27.
• Hyari K, El-Rayes K. Optimal planning and scheduling for repetitive construction projects. Journal of Management in Engineering ASCE 2006; 22(1): 11-19.
• Ipsilandis P. Multiobjective linear programming model for scheduling linear repetitive projects. Journal of Construction Engineering and Management ASCE 2007; 133(6): 417-424.
• Liu S, Wang C. Optimizing linear project scheduling with multi-skilled crews. Automation in Construction 2012; 24: 16-23.
• El-Rayes K. Object-oriented model for repetitive construction scheduling. Journal of Construction Engineering and Management ASCE 2001; 127(3): 199-205.
• Zhang H, Li H, Tam CM. Heuristic scheduling of resource‐constrained, multiple‐mode and repetitive projects. Construction Management and Economics 2016; 24(2): 159-169.
• Senouci A, Al-Derham H. Genetic algorithm-based multi-objective model for scheduling of linear construction projects. Advances in Engineering Software 2008; 39(12): 1023-1028.
• Long L, Ohsato A. A genetic algorithm-based method for scheduling repetitive construction projects. Automation in Construction 2009; 18(4): 499-511.
• Hyari K, El-Rayes K, El-Mashaleh M. Automated trade‐off between time and cost in planning repetitive construction projects. Construction Management and Economics 2009; 27(8): 749-761.
• Eid M, Abdelrazek M, Elbeltagi E. Multi-objective repetitive activities projects scheduling using Genetic Algorithms. CRC Press Boca Raton FL 2012; 331-335.
• Kaveh A, Farivar R, Sajjad M. Many-objective optimization for construction project scheduling using non-dominated sorting differential evolution algorithm based on reference points. Scientia Iranica, 2021; 28(6): 3112-3128.
• Bettemir ÖH, Yücel T. Simplified solution of time-cost trade-off problem for building constructions by linear scheduling. Jordan Journal of Civil Engineering 2023: 17(2).
• Bakry I, Moselhi O, Zayed T. Optimized scheduling and buffering of repetitive construction projects under uncertainty. Engineering, Construction and Architectural Management 2016; 23(6): 782-800.
• Salama T, Moselhi O. Multi-objective optimization for repetitive scheduling under uncertainty. Engineering, Construction and Architectural Management 2019; 27(7): 1294-1320.
• Huang R, Halpin D. Graphically based LP modelling for linear scheduling analysis: the POLO system. Engineering, Construction and Architectural Management 2000; 7(1): 41-51.
• Srisuwanrat C, Ioannou P. Optimal scheduling of probabilistic repetitive projects using completed unit and genetic algorithms. Winter Simulation Conference Washington DC 2007; 2151-2158.
• Bragadin M, Kahkonen K. Heuristic solution for resource scheduling for repetitive construction projects. Management and Innovation for a Sustainable Built Environment Amsterdam The Netherlands 2011.
• Hassan A, El-Rayes K, Attalla M. Stochastic scheduling optimization of repetitive construction projects to minimize project duration and cost. International Journal of Construction Management 2023; 23(9): 1447-1456.
• Zou X, Rong Z. Resource-constrained repetitive project scheduling with soft logic. Engineering, Construction and Architectural Management 2024 (ahead-of-print).
• Çevikbaş M, Işık Z. Overarching review on delay analyses in construction projects. Buildings 2021; 11(3): 109.
• Çevikbaş M, Işık Z. Detecting the most appropriate delay analysis methods for mega airport projects. Engineering, Construction and Architectural Management 2023; 30(6): 2463-2480.
• Çevikbaş M, Okudan O, Işık Z. New delay-analysis method using modified schedule and modified updated schedule for construction projects. Journal of Construction Engineering and Management 2022; 148(11): 1-18.
• Thomas H, Mathews C, Ward J. Learning curve models of construction productivity. Journal of Construction Engineering and Management ASCE 1986; 112(2): 245-258.
• Agrama FA. Multi-objective genetic optimization for scheduling a multi-storey building. Automation in Construction 2014; 44: 119-128.
• Hegazy T. Computerized system for efficient scheduling of highway construction. Transportation Research Record: Journal of the Transportation Research Board, No. 1907, Transportation Research Board of the National Academies, Washington DC 2005; 8-14.