حل مساله تبادل زمان ـ هزینه ـ کیفیت پروژه‌ها در حالت احتمالی با در نظرگرفتن راه حل های ممکن
محورهای موضوعی :
مدیریت صنعتی
S. Farid Mousavi
1
,
Kaveh Khalili-Damghani
2
,
Farnaz Rezapour
3
,
Arezoo Gazori-Nishabori
4
1 - Department of Operations Management and Information Technology,
Kharazmi University, Tehran, Iran.
2 - Department of Industrial Engineering
South-Tehran Branch, Azad University, Tehran, Iran
3 - Department of Industrial Engineering
South-Tehran Branch, Azad University, Tehran, Iran.
4 - Industrial Engineering, Department of Industrial Engineering
South-Tehran Branch, Azad University, Tehran, Iran
تاریخ دریافت : 1400/08/02
تاریخ پذیرش : 1401/03/05
تاریخ انتشار : 1401/05/03
کلید واژه:
برنامه‌ریزی احتمالی,
برنامه ریزی چند هدفه,
انقطاع‌پذیری,
روابط پیش‌نیازی عمومی,
چکیده مقاله :
مدیران پروژه همواره به دنبال اتخاذ تصمیماتی هستند که بتوانند پروژه‌های خود را در کوتاه‌ترین زمان ممکن، با کمترین هزینه و با کیفیتی بالا به انجام برسانند. لیکن باید توجه داشت که در مسائل واقعی با شرایطی مواجه می‌شویم که پیش‌بینی‌های ما تحت تاثیر سایر عوامل از آنچه در عمل اتفاق می‌افتد فاصله می‌گیرد در چنین شرایطی عملاً برخی یا تمامی پارامترهای مرتبط با یک مساله مورد بررسی به وسیله متغیرهایی بیان می‌شوند که به صورت قطعی تعریف نشده‌اند. از این رو در نظر گرفتن اثر پارامترهای تصادفی در حل مساله تبادل زمان ـ هزینه ـ کیفیت دارای اهمیت بسیار زیادی می‌باشد. در این مقاله سعی داریم تا مدل مساله تبادل زمان ـ هزینه ـ کیفیت ارائه شده را در حالت تصادفی مورد توجه قرار دهیم. به این منظور برخی از پارامترهای مدل مورد اشاره را به صورت تصادفی فرض می‌کنیم. سپس به منظور حل مدل تصادفی از رویکرد برنامه‌ریزی مقید شده تصادفی استفاده خواهیم کرد. به هنگام مواجهه با توابع هدف چندگانه از میان روش‌های بهینه‌سازی مسائل چندهدفه به روش برنامه‌ریزی آرمانی خواهیم پرداخت و در نهایت مدل برنامه‌ریزی آرمانی مقید شده تصادفی را ارائه خواهیم نمود. معدل برنامه ریزی قطعی مدل ارائه شده ارائه می‌شود و در نهایت با استفاده از نرم افزار گمز و با یک مثال عددی، مدل ارائه شده حل و نتایج حاصل از آن مورد بررسی قرار خواهد گرفت.
چکیده انگلیسی:
Time-cost-quality trade-off project scheduling problem is one of the most important and practical problems in project management discipline. Project Managers interest in making decisions to accomplish the project with minimum cost, minimum time, and maximum quality. Unfortunately, in real life problems, the estimation of time, cost, and quality may be mixed with uncertainty. These parameters may be far from their estimated values. So, considering uncertain parameters in time-cost-quality project scheduling is essential. In this paper, a probabilistic version of time-cost-quality trade –off problem is proposed. Some parameters of the proposed model are assumed to be probabilistic. The probabilistic nature of the proposed model is handled using stochastic chance constraint programming. The multi-objective nature of the problem is handled using goal programming. Finally, the stochastic chance constraint goal programming is proposed. The deterministic equivalence of proposed stochastic model is presented. A numerical example is analyzed using GAMS software and results are investigated.
منابع و مأخذ:
Charnes, A., and Cooper, W. (1963). Deterministic equivalents for optimizing and satis_cing under chance constraints. Operational Research, 11: 18-39.
Deckro, R. F., Hebert, J. E., Verdini, W. A., Grimsrud, P. H., & Venkateshwar, S. (1995). Nonlinear time/cost tradeoff models in project management. Computers & Industrial Engineering, 28(2), 219-229.
Ekhtiari, Mustafa (2011). Possible multi-objective planning to optimize the issue of determining the amount of manpower in workshop production systems. Industrial Management Studies, 8 (19), 189-216.
Eshtehardian, E., Afshar, A., Abbasnia, R. (2008). Time-cost optimization: using GA and fuzzy sets theory for uncertainties in cost. Constr. Econ, 26: 679-691.
Golshani, Mojtaba (2015). Project planning and control. Tehran: Zaman Publication.
Ibrahim Nejad, Saadullah., Ahmadi, Vahid & Javanshir, Hassan (2013). Balancing cost, time, and quality measures in a CPM network using fuzzy logic and genetic algorithms. International Journal of Industrial Engineering and Production Management, 24 (3): 362-376.
Isikyildiz, S., Akcay, C. (2020). Multi- objective optimization of time-cost-quality in construction ptojects using genetic algorithm. Revista la Construccion, 19(3).
Mehdizadeh, Ismail., Mohsenian, Omid (2011). Solving the time-cost and quality balance problem using multi-objective stochastic programming. Journal of Industrial Engineering and Management Sharif, 28 (2).
Mungle, S., and Benyoucef, L., Son, Y., and 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.
Orm, M.B., Jeunet, J. (2018). Time-cost-quality trade-off problems: A survey exploring the assessment of quality. Computers and Industrial Engineering. 118. 319-328.
Rahimi, M., and Iranmanesh, H. (2008). Multi objective particle swarm optimization for a discrete time, cost and quality trade-off problem. World Applied Sciences Journal, 4(2): 270–276.
Tavana, M., Abtahi, A., Khalili-Damghani, K. (2013). A new multi-objective multi-mode model for solving preemptive time–cost–quality trade-off project scheduling problem. Expert Systems with Applications.
Wuliang, P., & Chengen, W. (2009). A multi-mode resource-constrained discrete time–cost tradeoff problem and its genetic algorithm-based solution. International journal of project management, 27(6), 600-609.
Wood, D.A. (2017). Gas and oil project time-cost-quality tradeoff: Integarted stochastic and fuzzy multi-objective optimization applying a memetic, nondominated, sorting algorithm. Journal of Natural Gas Science and Engineering, 45: 143-164.
Yildirim, H.A., Akcay, C. (2019). Time-cost optimization model proposal for construction projects with genetic algotithm and fuzzy logic approach. Revista de la Construction, 18(3).
Zhang, H., and Xing, F. (2010). Fuzzy-multi-objective particle swarm optimization for time–cost–quality tradeoff in construction. Automation in Construction, 19(8): 1067–1075.
Zhang, L., Du, J., and Zhang, Sh. (2014). Solution to the time-cost-quality trade-off problem in construction projects based on immune genetic particle swarm optimization. Journal of Management in Engineering, 30(2): 163-172.
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Charnes, A., and Cooper, W. (1963). Deterministic equivalents for optimizing and satis_cing under chance constraints. Operational Research, 11: 18-39.
Deckro, R. F., Hebert, J. E., Verdini, W. A., Grimsrud, P. H., & Venkateshwar, S. (1995). Nonlinear time/cost tradeoff models in project management. Computers & Industrial Engineering, 28(2), 219-229.
Ekhtiari, Mustafa (2011). Possible multi-objective planning to optimize the issue of determining the amount of manpower in workshop production systems. Industrial Management Studies, 8 (19), 189-216.
Eshtehardian, E., Afshar, A., Abbasnia, R. (2008). Time-cost optimization: using GA and fuzzy sets theory for uncertainties in cost. Constr. Econ, 26: 679-691.
Golshani, Mojtaba (2015). Project planning and control. Tehran: Zaman Publication.
Ibrahim Nejad, Saadullah., Ahmadi, Vahid & Javanshir, Hassan (2013). Balancing cost, time, and quality measures in a CPM network using fuzzy logic and genetic algorithms. International Journal of Industrial Engineering and Production Management, 24 (3): 362-376.
Isikyildiz, S., Akcay, C. (2020). Multi- objective optimization of time-cost-quality in construction ptojects using genetic algorithm. Revista la Construccion, 19(3).
Mehdizadeh, Ismail., Mohsenian, Omid (2011). Solving the time-cost and quality balance problem using multi-objective stochastic programming. Journal of Industrial Engineering and Management Sharif, 28 (2).
Mungle, S., and Benyoucef, L., Son, Y., and 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.
Orm, M.B., Jeunet, J. (2018). Time-cost-quality trade-off problems: A survey exploring the assessment of quality. Computers and Industrial Engineering. 118. 319-328.
Rahimi, M., and Iranmanesh, H. (2008). Multi objective particle swarm optimization for a discrete time, cost and quality trade-off problem. World Applied Sciences Journal, 4(2): 270–276.
Tavana, M., Abtahi, A., Khalili-Damghani, K. (2013). A new multi-objective multi-mode model for solving preemptive time–cost–quality trade-off project scheduling problem. Expert Systems with Applications.
Wuliang, P., & Chengen, W. (2009). A multi-mode resource-constrained discrete time–cost tradeoff problem and its genetic algorithm-based solution. International journal of project management, 27(6), 600-609.
Wood, D.A. (2017). Gas and oil project time-cost-quality tradeoff: Integarted stochastic and fuzzy multi-objective optimization applying a memetic, nondominated, sorting algorithm. Journal of Natural Gas Science and Engineering, 45: 143-164.
Yildirim, H.A., Akcay, C. (2019). Time-cost optimization model proposal for construction projects with genetic algotithm and fuzzy logic approach. Revista de la Construction, 18(3).
Zhang, H., and Xing, F. (2010). Fuzzy-multi-objective particle swarm optimization for time–cost–quality tradeoff in construction. Automation in Construction, 19(8): 1067–1075.
Zhang, L., Du, J., and Zhang, Sh. (2014). Solution to the time-cost-quality trade-off problem in construction projects based on immune genetic particle swarm optimization. Journal of Management in Engineering, 30(2): 163-172.
