Time-Cost-Quality trade off in Critical Chain Method with multi mode activities by Multi Objective Particle Swarm Optimization

Document Type : Original Article

Authors

1 PhD student, Babol University of Technology, Babol, Iran

2 Assistant Professor, faculty of civil engineering, Babol University of technology

3 Assistant Professor, Department of Project and Construction Management, Tarbiat Modares University, Tehran, Iran

4 Assisstat Professor, Department of Civil Engineering, Babol University of Technology, Babol, Iran

Abstract

Believing in the fact that an activity can be performed through several methods or states, or that there may be several executive states for activities with different numbers of resources in real conditions, the scheduling obtained from different methods with different combinations of time, resources, and quality need to be evaluated and optimized. These are referred to as project scheduling problems with multistate resources. On the other hand, application of the theory of constraints to project management has led to the development of a novel approach in project planning and control known as the critical chain. The present paper seeks to use the critical chain technique and simultaneous time-cost-quality trade off. In this study, the multi-objective problem of time-cost-quality trade off has been solved using the high capability of the multi-objective particle swarm algorithm in optimization and the critical chain technique, so that the most appropriate sequence and executive state of activities is found such that time, cost, and quality are optimized and close to reality. The optimization algorithm programming was coded in the MATLAB software, and the target results were extracted. For evaluation of the proposed model, two case studies with 7 and 18 activities have been solved. Furthermore, a project with 60 activities where the time-cost-quality trade off had been established were used for validation of the proposed algorithm, and new results were extracted. The results demonstrated that the developed algorithm has had correct, proper performance, in such a way that it is capable of generating several Pareto solutions with different time, cost, and quality values. Furthermore, the results have been reported separately based on the best time, cost, and quality, which makes it possible for the project managers to select the better solutions given their priorities in the project.

Keywords

Main Subjects


[1] Park, W. R., Chapin, W. B. (1992). “Construction bidding: Strategic pricing for profit”,Wiley, New York, 1992.
[2] Alkass, S., Mazerolle, M., Harris, F., (1996) ‘‘Construction delay analysis techniques’’ ,Construction Management Economics., Vol. 14, No. 5, pp. 375–394, Doi: 10.1080/014461996373250.
[3] Sonmez, R, Bettemir, O. H, (2012) “A hybrid genetic algorithm for the discrete time–cost trade-off problem”, Expert Systems with Applications, Vol 39, No 13, 11428–11434, Doi: 10.1016/j.eswa.2012.04.019.
[4] PMI. (2013), "A guide to the project management body of knowledge: PMBOK Guide.", 5th ed. USA: Project Management Institute Inc.
[5] Goldratt, E. M. , (1997). “Critical Chain”, The North River Press Publishing Corporation, Great Barrington
[6] Rand , K. , (2000), "Critical chain: the Theory of constraints applied to project management" ,International Journal of Project Management, Vol 18, No 3, 173-177, Doi: 10.1016/S0263-7863(99)00019-8.
[7] Raz, T, Barnes, R, Dvir, D, (2003), "A critical look at critical chain project management", Project management journal, Vol 34, No 4, 24-32, Doi: 10.1109/EMR.2004.25048.
[8] Kuchta, D ," The critical chain method in project management-A formal description", Badania Operacyjneide I Decyzje, Vol 1, 37-51, 2004.
[9] Leach, L, (2000), "Critical chain project management improves project performance", Advanced Project Institute.
[10] Herroelen, W, Leus, R, Demeulemeester, E, (2002), "Critical chain project scheduling do not oversimplify", Project Management Journal, Vol 33, No 4, 48-60.
[11] Juring, J, (2004), "Benefits of a critical chain – a System Dynamics based study", Second World Conference on POM and 15th Annual POM Conference, Cancun, Mexico.
[12] Trietsch Dan, (2005), "Why a Critical Path by Any Other Name Would Smell Less Sweet", Project Management Institute, Vol 36, No1, 27-36
[13] Shen, L, Chua, D, (2008), "An Investigation of Critical Chain and Lean Project Scheduling",16th Annual Conference of the International Group for Lean Construction, United States.
[14] startton, R, (2009), "Critical Chain Project Management Theory and Practice", POMS 20th Annual Conference, USA.
[15] Wei-Xin, W, Xu,W, Xian-Long, G, Lei, D, (2014) "Multi-objective optimization model for multi-project scheduling on critical chain", Advances in Engineering Software, Vol 68, 33–39, Doi: 10.1016/j.advengsoft.2013.11.004.
[16] Ghoddousi, P., Ansari, R. & Makui, A., (2016), “A risk-oriented buffer allocation model based on critical chain project management”, KSCE Journal of Civil Engineering, 1-13, Doi:10.1007/s12205-016-0039-y.
[17] Vanhoucke, M. (2016). “Buffer management” Integrated Project Management Sourcebook. Springer International Publishing, pp. 155-193.
[18] Hartmann, S. and Briskorn, D. (2010). “A survey of variants and extensions of the resource-constrained project scheduling problem.” European Journal of operational research , Vol. 207, No. 1, PP. 1-14.
[19] Li, H. Zhang, H.(2013) "Ant colony optimization-based multi-mode scheduling under renewable and nonrenewable resource constraint", Automation in construction, Volume 35, 431-438.
[20] Li, H. Zhang, H.(2013) " Ant colony optimization-based multi-mode scheduling under renewable and nonrenewable resource constraint",Automation in construction, Volume 35, 431-438.
[21] De, P., Dunne, E., Ghosh, J., & Wells, C. (1997). “Complexity of the discrete time/cost trade-off problem for project networks” ,Operations Research, 45, 302–306.
[22] Taheri Amiri, M.J, Haghighi, F, Eshtehardian, E, Abessi, O, (2017), “Optimization of Time, Cost, and Quality in Critical Chain Method Using Simulated Annealing”, International Journal of Engineering, Vol 30, No 5, pp. 705-713, Doi: 10.5829/idosi.ije.2017.30.05b.00.
[23] Mungle, S, Benyoucef, L, Son, Y.J, 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, 1953–1966.
[24] Afruzi, E.N., Najafi, A.A., Roghanian, E., Mazinani, M. (2014) “A Multi-Objective Imperialist Competitive Algorithm for solving discrete time, cost and quality trade-off problems with mode-identity and resourceconstrained situations”, Computers & Operations Research, No. 50, pp. 80 – 96.
[25] Tavana, M, Abtahi, A.R, Khalili-Damghani, K, (2014) “A new multi-objective multi-mode model for solving preemptive time–cost–quality trade-off project scheduling problems”, Expert System with Applications, Vol 41, Issue 4, 1830-1846.
[26] Monghasemi, S, Nikoo, M.R, Khaksar, M.A, Adamowski, F,J, (2015) “A Novel Multi Criteria Decision Making Model for Optimizing Time-Cost-Quality Trade-off Problems in Construction Projects”, Expert System with Applications, Vol 42, Issue 6, 3089-3104.
] 27 [ موشخیان، سیامک و نجفی، امیرعباس، " بهینهسازی سبد سرمایهگذاری با استفاده از الگوریتم چند هدفه ازدحام ذرات برای مدل احتمالی چند
دورهای میانگین نیم واریانس چولگی"، مجله مهندسی مالی و مدیریت اوراق بهادار، شمارهی بیست و سوم، تابستان 1314 ، دانشگاه آزاد اسلامی - - -
واحد تهران مرکزی.
[28] Tran, D. H., Cheng, M. Y., Cao, M. T., “Hybrid multiple objective artificial bee colony with differential evolution for the time-cost-quality trade off problem”, Knowledge-Based Systems, Vol 74, 176-186.
[29] Feng, C., Liu, L., and Burns, S. (2000) "Stochastic Construction Time Cost Trade-off Analysis", Journal of Computing in Civil Engineering, Vol 14, Issue 2, 117-126.
[30] Feng, C., Liu, L., and Burns, S. (1997) "Using Genetic Algorithm to Solve Construction Time-Cost Trade-off Problems”, Journal of Computing in Civil Engineering , Vol 11, Issue 3, 184-189.
[31] Zhang, L., Du, J., and Zhang, S (2013) "A Solution to Time-Cost-Quality Trade-off Problem in Construction Projects Based on Immune Genetic Particle Swarm Optimization", Journal of Management in Engineering., Vol 30, Issue 2,1943-5479.
[32] Xiong, Y. and Kuang, Y, (2008) "Applying an Ant Colony Optimization Algorithm –Based Multi Objective Approach for Time-Cost Trade-Off.", Journal of construction Engineering and management, Vol 134, Issue 2, 153-156.
] 33 [ اشتهاردیان، احسان اله، موازنه زمان هزینه با استفاده از الگوریتم ژنتیک و منطق فازی در بیان عدم قطعیتها، رساله برای دریافت درجه دکترا، -
- .) عمران مدیریت ساخت، دانشگاه علم و صنعت ایران ) 1317
[34] Hegazy T., (1999) “Optimization of construction time-cost trade-off analysis using genetic algorithms”, Canidian Journal of Civil Engineering, Vol.26, PP. 685-697.
[35] Elbeltagi, E, Hegazy, T, Grierson, D, (2005) "Among Five Evolutionary-Based Optimization Algorithms", Advanced Engineering Informatics, Vol 19,Issue 1, 43-53.
[36] El-Rayes K, Amr Kandil A. . (2005). "Time-Cos-Quality Trade-off Analysis for Highway Constructions". Construction Engineering Management., ASCE, 131(4):447-486.
  • Receive Date: 18 July 2017
  • Revise Date: 21 November 2017
  • Accept Date: 23 November 2017
  • First Publish Date: 22 June 2019