The Combinatorial Multi-Mode Resource Constrained Multi-Project Scheduling Problem

Document Type: Research Paper

Authors

1 West Virginia University, Morgantown, WV, USA

2 Federal Center for Technological Education of Rio de Janeiro, Rio de Janeiro, Brazil

Abstract

This paper presents the formulation and solution of the Combinatorial Multi-Mode Resource Constrained Multi-Project Scheduling Problem. The focus of the proposed method is not on finding a single optimal solution, instead on presenting multiple feasible solutions, with cost and duration information to the project manager. The motivation for developing such an approach is due in part to practical situations where the definition of optimal changes on a regular basis. The proposed approach empowers the project manager to determine what is optimal, on a given day, under the current constraints, such as, change of priorities, lack of skilled worker. The proposed method utilizes a simulation approach to determine feasible solutions, under the current constraints. Resources can be non-consumable, consumable, or doubly constrained. The paper also presents a real-life case study dealing with scheduling of ship repair activities.

Keywords

Main Subjects


Abrantes, R., Figueiredo, J., (2015). Resource management process framework for dynamic NPD portfolios. International Journal of Project Management, Vol. 33(6),pp. 1274-1288.

Alcaraz, J., Maroto, C., Ruiz, R., (2003). Solving the multi-mode resource-constrained project scheduling problem with genetic algorithms. Journal of the Operational Research Society, Vol.54, pp. 614–626.

AlSehaimi, A., Koskela, L., and Tzortzopoulos, P., (2013). Need for Alternative Research Approaches in Construction Management: Case of Delay Studies. Journal of Management in Engineering, Vol.29(4), pp. 407–413.

Araúzo, J., Pajares, J., Lopez-Paredes, A., (2010). , Simulating the dynamic scheduling of project portfolios. Simulation Modelling Practice and Theory, Vol. 18(10), pp. 1428-1441.

Baumann, P., Trautmann, N., (2013). Optimal scheduling of work-content constrained projects. In Proceedings of the IEEE international conference on industrial engineering and engineering management.

Belkaid, F., Sari, Z., & Souier, M. (2013). A genetic algorithm for the parallel machine scheduling problem with consumable resources. International Journal of Applied Metaheuristic Computing (IJAMC), Vol.4(2), pp. 17-30.

Belkaid, F., Yalaoui, F., & Sari, Z. (2016). An Efficient Approach for the Reentrant Parallel Machines Scheduling Problem under Consumable Resources Constraints. International Journal of Information Systems and Supply Chain Management (IJISSCM), Vol. 9(3), pp. 1-25.

Belkaid, F., Yalaoui, F., & Sari, Z. (2016). Investigations on Performance Evaluation of Scheduling Heuristics and Metaheuristics in a Parallel Machine Environment. In Metaheuristics for Production Systems (pp. 191-222). Springer International Publishing.

Be┼čikci, U., Bilge, U., Ulusoy, G., (2015). Multi-mode resource constrained multi-project scheduling and resource portfolio problem. European Journal of Operational Research, Vol. 240(1), pp. 22-31.

Bianco, L., Caramia, M., (2013). A new formulation for the project scheduling problem under limited resources. Flexible Services and Manufacturing Journal, Vol. 25, pp. 6–24.

Pinha, Ahluwalia and Senna Bouleimen, K., Lecocq, H., (2003). A new efficient simulated annealing algorithm for the resource-constrained project scheduling problem and its multiple mode version. European Journal of Operational Research, Vol. 149(2), pp. 268–281.

Browning, T., Yassine, A., (2010). Resource-constrained multi-project scheduling: Priority rule performance revisited. International Journal of Production Economics, Vol. 126(2), pp. 212–228.

Brucker, P., Drexl, A., Mohring, R., Neumann, K., Pesch, E., (1999). Resource-constrained project scheduling: notation, classification, models, and methods. European Journal of Operational Research, Vol. 112, pp. 3–41.

Carlier, J., Moukrim,A., & Xu, H. (2009). The project scheduling problem with production and consumption of resources: A list-scheduling based algorithm. Discrete Applied Mathematics, Vol. 157(17), pp. 3631-3642.

Chen, P., Shahandashti, S., (2009). Hybrid of genetic algorithm and simulated annealing for multiple project scheduling with multiple resource constraints. Automation in Construction, Vol. 18(4), pp. 434-443.

Chryssolouris, G., (2005). Manufacturing Systems: Theory and Practice, 2nd Edition NewYork, Springer-Verlag. DoN, 2013. http://www.onr.navy.mil/~/media/Files/Funding-Announcements/BAA/2013/13-020.ashx

Drexl, A., Nissen, R., Patterson, J., Salewski, F., (2000). Progen/px – An instance generator for resource-constrained project scheduling problems with partially renewable resources and further extensions. European Journal of Operational Research, 125(1), 59–72.

Elmaghraby, S., (1977). Task networks: Project planning and control by network models. Wiley, New York. Fundeling, C., Trautmann, N., 2010. A priority-rule method for project scheduling with work-content constraints. European Journal of Operational Research, Vol. 203, pp. 568–574.

Hartmann, S., Briskorn, D., (2010). , A survey of variants and extensions of the resource-constrained project scheduling problem, European Journal of Operational Research, Vol. 207(1), pp. 1-14.

Józefowska, J., Weglarz, J., (2006). Perspectives in Modern Project Scheduling. Springer, New York.

Jozefowska, J., Mika, M., Rozycki, R., Waligora, G., Weglarz, J., (2001). Simulated annealing for multi-mode resource-constrained project scheduling. Annals of Operations Research, Vol. 102, pp. 137–155.

Kolisch, R., Drexl, A., (1997). Local for multi-mode resource-constrained project. IIE Transactions, Vol. 29(11), pp.  987–999.

Laslo, Z., Goldberg, A., 2008. Resource allocation under uncertainty in a multi-project matrix environment: Is organizational conflict inevitable? International Journal of Project Management, Vol. 26(8), pp. 773-788.

Lau, S., Lu, M., and Poon, C. (2014). Formalized Approach to Discretize a Continuous Plant in Construction Simulations. Journal of Construction Engineering and Management, Vol. 140(8), 04014032.

Leadership, (2013), http://ec.europa.eu/enterprise/sectors/maritime/files/shipbuilding/leadership2020-final-report_en.p df

Lee, K., Lei, L., Pinedo, M., & Wang, S. (2013). Operations scheduling with multiple resources and transportation considerations. International Journal of Production Research, Vol. 51(23-24), pp. 7071-7090.

Maenhout, B., Vanhoucke, M., (2015), “An exact algorithm for an integrated project staffing problem with a homogeneous workforce”, Journal of Scheduling, p-1-27, August-2015.

MARAD, (2013). http://www.marad.dot.gov/documents/MARAD_Econ_Study_Final_Report_ 2013.pdf MP (2015), http://office.microsoft.com/en-us/project/

Naber, A., Kolisch, R., 2014. MIP models for resource-constrained project scheduling with flexible resource profiles. European Journal of Operational Research, Vol. 239(2), pp. 335-348.

NRC (2009), http://www.nationalacademies.org/nrc/

NSRP, (2013), http://www.nsrp.org/2-Solicitation_Documents/RA%2012-01_FINAL-v2.pdf

Peteghem, V., Vanhoucke, M., (2010). A genetic algorithm for the preemptive and non-preemptive multi-mode resource-constrained project scheduling problem. European Journal of Operational Research, Vol. 201(2), pp. 409–418.

Pinha, D., (2015), “Short-Term Resource Allocation and Management”, Ph.D. dissertation, West Virginia University.

Pinha, D., Ahluwalia, R., Carvalho, A., (2015), “Parallel Mode Schedule Generation Scheme”, 2015 IFAC Symposium on Information Control in Manufacturing, Ottawa, Canada.

Pinha, D., Ahluwalia, R., Carvalho, A., Senna, P., (2015), “Supply Chain Scheduling: A Motorcycle Assembly Case Study”, 2015 IFAC Symposium on Information Control in Manufacturing, Ottawa, Canada.

Pinha, D, Ahluwalia, R, (2014), “Decision Support System for Production Planning in the Ship Repair Industry”. Industrial and Systems Engineering Review Journal, [S.l.], Vol. 2, No. 1, pp. 52-61, jul. 2014. ISSN 2329-0188

Pinha, D., Ahluwalia, R, (2013), Proceedings of the Industrial and System Engineering World Conference, “Decision Support System for Repair Shipyard Industry”, Las Vegas, USA.

Pinha, D., De Queiroz, M.H., Cury, J. E R, (2011). Optimal scheduling of a repair shipyard based on Supervisory Control Theory. Proceedings of the IEEE Conference on Automation Science and Engineering (CASE), pp.39-44.

PMI, (2013). A Guide to the Project Management Body of Knowledge, Fifth Edition, Project Management Institute.

PMI KPMG, (2013). “Study on project schedule and cost overruns” http://www.pmi.org.in/downloads/PMI_KPMG_2013.pdf

Primavera, (2015), https://docs.oracle.com/cd/E16688_01/Moving_From_P3_to_P6/MovingfromP3toP6.pdf

Pritsker, A., Watters, L., Wolfe, P., (1969). Multi project scheduling with limited resources: A zero-one programming approach. Manage. Sci., Vol. 16, pp. 93–108.

Ranjbar, M., Kianfar, F., (2010). Resource-constrained project scheduling problem with flexible work profiles: A genetic algorithm approach. Transaction E: Industrial Engineering, Vol.17, pp. 25–35.

Pinha, Ahluwalia and Senna Rehm, M., Thiede, J., (2012). A survey of recent methods for solving project scheduling problems. Technische Universität Dresden, Fakultät Wirtschaftswissenschaften.

Reichelt, K., Lyneis, J., (1999). The dynamics of project performance: benchmarking the drivers of cost and schedule overrun. European Management Journal, Vol. 17(2), pp. 135-150.

Rieck, J., Zimmermann, J., Gather, T., (2012). Mixed-Integer Linear Programming for Resource Leveling Problems. European Journal of Operational Research, Vol. 221, pp. 27-37.

Sabzehparvar, M., Seyed-Hosseini, S., (2008). A mathematical model for the multimode resource-constrained project scheduling problem with mode dependent time lags. Journal of Supercomputing, Vol. 44(3), pp. 257–273.

Siu, M., Lu, M., AbouRizk, S., (2015). Zero-One Programming Approach to Determine Optimum Resource Supply under Time-Dependent Resource Constraints. Journal of Computing in Civil Engineering, 10.1061/ (ASCE) CP.1943-5487.0000498 , 04015028.

Speranza, M. G, and C. Vercellis, (1993). Hierarchical models for multi-project planning and scheduling. European Journal of Operational Research, Vol. 64(2), pp. 312–325.

Vanhoucke, M., (2013). Project Management with Dynamic Scheduling, Baseline Scheduling, Risk Analysis and Project Control. 2nd ed. 2013, XVIII, 318 p. 123 illus.

Wongwai, N., Malaikrisanachalee, S., (2011). Augmented heuristic algorithm for multi-skilled resource scheduling. Automation in Construction, Vol. 20(4), pp. 429-445.

Xu, J., Feng. C., (2014). Multimode Resource-Constrained Multiple Project Scheduling Problem under Fuzzy Random Environment and Its Application to a Large Scale Hydropower Construction Project. The Scientific World Journal, Article ID 463692.

Xue, H., Wei, S., Wang, Y., (2010). Resource-constrained multi-project scheduling based on ant colony neural network. Apperceiving Computing and Intelligence Analysis (ICACIA) International Conference, pp.179-182.

Zhang, L., Sun, R., (2011). An improvement of resource-constrained multi-project scheduling model based on priority-rule based heuristics. Service Systems and Service Management (ICSSSM), 8th International Conference, pp.1-5.