حل مسئله زمانبندی پروژه با محدودیت منابع چندهدفه در حالت چند مد با الگوریتم زنبورهای عسل چندهدفه
محورهای موضوعی :
مدیریت صنعتی
Amir Sadeghi
1
,
Sina Namazi
2
,
Zahra Ghorajehlo
3
,
Behnam Rezvanpour
4
1 - Faculty of management and accounting, South Tehran Branch, Islamic Azad University, Tehran, Iran
2 - Karaj Branch, Islamic Azad University, Karaj, Iran
3 - Isfahan University of Technology, Isfahan, Iran
4 - Rasht Branch, Islamic Azad University, Rasht, Iran
تاریخ دریافت : 1394/03/24
تاریخ پذیرش : 1395/04/28
تاریخ انتشار : 1395/06/04
کلید واژه:
NSGA-II,
Multi-objective,
Project Scheduling,
چندهدفه,
الگوریتم NSGA-II,
زمانبندی پروژه,
RCPSP,
محدودیت منابع,
الگوریتم MOBEE,
Resource constraints,
MOBEE algorithm,
چکیده مقاله :
مساله زمانبندی پروژه با منابع محدود، در واقع کلی ترین مساله زمانبندی است. مسائل زمانبندی کارگاهی ، جریان کارگاهی ، زمانبندی و سایر مسائل زمانبندی همگی زیر مجموعه ای از این مسئله به حساب می آیند. در این مقاله مسئله زمانبندی پروژه با محدودیت منابع در حالت چند مد و روابط پیش نیازی جزئی در حالت مدل چندهدفه پیشنهاد شده است. در جهت کاربردی تر کردن بیش از پیش این مسئله مشهور اهداف مهم و کاربردی از قبیل کمینه کردن زمان اتمام پروژه و بیشینه کردن کیفیت انجام فعالیت های پروژه و کمینه کردن هزینه کل پروژه در نظر گرفته شده است. پس از اعتبار دهی مدل با استفاده از الگوریتم زنبورهای عسل به حل این مدل چند هدفه پیشنهادی، پرداخته شده است و نتایج عملکرد، با الگوریتم NSGA-II مقایسه شده است. نتایج نشان دهنده این است که الگوریتم پیشنهادی عملکرد مناسبی در حل این گونه مسائل داشته است.
چکیده انگلیسی:
Resource Constrained Project Scheduling Problem (RCPSP) is the most general scheduling problem. Job shop scheduling, flow shop scheduling and other scheduling problems are the subsets of RCPSP. The present paper examines the multimode multi-objective resource-constrained project scheduling problem (RCPSP) with partial precedence relations. To enhance the practical aspects of this prominent problem, important practical purposes including minimizing the completion time of the project, maximizing the quality of project activities and minimizing the total cost of the project were considered. After validation of the model using the Bees Algorithm, the proposed multi-objective model was solved. The results obtained from the proposed model were compared with those obtained from NSGA-II. The results demonstrated the good performance of the proposed algorithm in solving RCPSPs.
منابع و مأخذ:
rucker وP., Drexl A., Mohring R., Neumann K., Pesch E. (1999). Resource-constrained project scheduling: Notation, classification, models, and methods, European Journal of Operational Research 112, 3–41.
Sprecher A. (1997). Exact algorithm for RCPSP in multi-mode case. OR Spectrum, Volume 19, Number 3, 195-203.
Abbasi B., Shadrokh S., Arkat J. (2006). Bi-objective resource-constrained project scheduling with obustness and makespan criteria, Applied Mathematics and Computation 180 (1), 146–152.
Nudtasomboon N., Randhawa S.U. (1997). Resource-constrained project scheduling with renewable and non-renewable resources and time-resource tradeoffs, Computers and Industrial Engineering 32 (1), 227–242.
Słowin´ ski R., B. Soniewicki, J. (1994). We_glarz, DSS for multiobjective project scheduling, European Journal of Operational Research, 79, (2), 220–229.
Viana A., de Sousa J.P. (2000). Using metaheuristics in multio-bjective resource constrained project scheduling, European Journal of Operational Research, 120 (2), 359–374.
Al-Fawzan M., Haouari M. (2005). A bi-objective model for robust resource constrained project scheduling, International Journal of Production Economics, 96, 175–187.
Davis K.R., A. Stam, R.A. Grzybowski. (1992). Resource constrained project scheduling with multiple objectives: A decision support approach, Computers and Operations Research, 19, (7), 657–669
Vos, S., Witt A. (2007). Hybrid flow shop scheduling as a multi-mode multi-project scheduling problem with batching requirements: A real-world application, International Journal of Production Economics, 105, (2), 445–458.
Hapke, M., Jaszkiewicz, A., Słowin´ski, R. (1998). Interactive analysis of multiple criteria project scheduling problems, European Journal of Operational Research, 107,315–324.
Dorner, K.F., Gutjahr, W.J., Hartl R.F., Strauss C., Stummer C. (2008). Nature-inspired metaheuristics for multiobjective activity crashing, Omega, 36, 1019–1037.
Nabrzynski J., We_glarz J. (1999). Knowledge-based multi-objective project scheduling problems, in: We_glarz , 383–411.
Pham D.T., Ashraf Afify. (2007). Ebubekir Koc Manufacturing cell formation using the Bees Algorithm". IPROMS Innovative Production Machines and Systems Virtual Conference, Cardiff, UK.
Francisco Ballestín, Rosa Blanco. (2011). Theoretical and practical fundamentals for multi-objective optimisation in resource-constrained project scheduling problems, Computers & Operations Research, 38(1), 51–62.
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Brucker وP., Drexl A., Mohring R., Neumann K., Pesch E. (1999). Resource-constrained project scheduling: Notation, classification, models, and methods, European Journal of Operational Research 112, 3–41.
Sprecher A. (1997). Exact algorithm for RCPSP in multi-mode case. OR Spectrum, Volume 19, Number 3, 195-203.
Abbasi B., Shadrokh S., Arkat J. (2006). Bi-objective resource-constrained project scheduling with obustness and makespan criteria, Applied Mathematics and Computation 180 (1), 146–152.
Nudtasomboon N., Randhawa S.U. (1997). Resource-constrained project scheduling with renewable and non-renewable resources and time-resource tradeoffs, Computers and Industrial Engineering 32 (1), 227–242.
Słowin´ ski R., B. Soniewicki, J. (1994). We_glarz, DSS for multiobjective project scheduling, European Journal of Operational Research, 79, (2), 220–229.
Viana A., de Sousa J.P. (2000). Using metaheuristics in multio-bjective resource constrained project scheduling, European Journal of Operational Research, 120 (2), 359–374.
Al-Fawzan M., Haouari M. (2005). A bi-objective model for robust resource constrained project scheduling, International Journal of Production Economics, 96, 175–187.
Davis K.R., A. Stam, R.A. Grzybowski. (1992). Resource constrained project scheduling with multiple objectives: A decision support approach, Computers and Operations Research, 19, (7), 657–669
Vos, S., Witt A. (2007). Hybrid flow shop scheduling as a multi-mode multi-project scheduling problem with batching requirements: A real-world application, International Journal of Production Economics, 105, (2), 445–458.
Hapke, M., Jaszkiewicz, A., Słowin´ski, R. (1998). Interactive analysis of multiple criteria project scheduling problems, European Journal of Operational Research, 107,315–324.
Dorner, K.F., Gutjahr, W.J., Hartl R.F., Strauss C., Stummer C. (2008). Nature-inspired metaheuristics for multiobjective activity crashing, Omega, 36, 1019–1037.
Nabrzynski J., We_glarz J. (1999). Knowledge-based multi-objective project scheduling problems, in: We_glarz , 383–411.
Pham D.T., Ashraf Afify. (2007). Ebubekir Koc Manufacturing cell formation using the Bees Algorithm". IPROMS Innovative Production Machines and Systems Virtual Conference, Cardiff, UK.
Francisco Ballestín, Rosa Blanco. (2011). Theoretical and practical fundamentals for multi-objective optimisation in resource-constrained project scheduling problems, Computers & Operations Research, 38(1), 51–62.
