Cost-efficient project management based on critical chain method with partial availability of resources

• Autorzy: Pawiński G. , Sapiecha K.
• Języki publikacji: EN

Abstrakty

EN

Cost-efficient project management based on Critical Chain Method (CCPM) is investigated in this paper. This is a variant of the resource-constrained project scheduling problem (RCPSP) when resources are only partially available and a deadline is given, but the cost of the project should be minimized. RCPSP is a well- known NP hard problem but originally it does not take into consideration the initial resource workload. A metaheuristic algorithm driven by a metric of a gain was adapted to solve the problem when applied to CCPM. Refinement methods enhancing the quality of the results are developed. The improvement expands the search space by inserting the task in place of an already allocated task, if a better allocation can be found for it. The increase of computation time is reduced by distributed calculations. The computational experiments showed significant efficiency of the approach, in comparison with the greedy methods and with genetic algorithm, as well as high reduction of time needed to obtain the results.

Słowa kluczowe

EN

project management and scheduling; resource allocation; resource constraints; metaheuristic algorithms; parallel processing

• Wydawca: Systems Research Institute, Polish Academy of Sciences
• Czasopismo: Control and Cybernetics
• Rocznik: 2014
• Tom: Vol. 43, no. 1
• Strony: 95--109
• Opis fizyczny: Bibliogr. 13 poz., rys., tab.

Twórcy

autor

Pawiński G.

• Department of Computer Science Kielce University of Technology al.1000-lecia P.P. 7, 25-314 Kielce Poland

autor

Sapiecha K.

• Department of Computer Science Kielce University of Technology al.1000-lecia P.P. 7, 25-314 Kielce Poland

Bibliografia

• 1. Bouleimen, K. and Lecocq, H. (2003) A new efficient simulated annealing algorithm for the resource constrained project scheduling problem and its multiple modes version. European Journal of Operational Research 149, 268–281.
• 2. Brucker, P., Knust, S., Schoo, A. and Thiele, O. (1998) A branch-and- bound algorithm for the resource constrained project scheduling problem. European Journal of Operational Research 107, 272–288.
• 3. Demeulemeester, E. L. and Herroelen, W. S. (1997) New benchmark results for the resource-constrained project scheduling problem. Management Science 43, 1485–1492.
• 4. Demeulemeester, E. L. and Herroelen, W. S. (2002) Project Scheduling. A Research Handbook. Springer.
• 5. Deniziak, S. (2004) Cost-efficient synthesis of multiprocessor heterogeneous systems. Control and Cybernetics 33, 341-355.
• 6. Goldratt, E.M. (1997) Critical Chain. The North River Press Publishing Corporation, Great Barrington.
• 7. Hartmann, S. (1998) A Competitive Genetic Algorithm for Resource-Constrained Project Scheduling. Naval Research Logistics 45, 733-750.
• 8. Hartmann, S. and Kolish, R. (2000) Experimental evaluation of state-of- the-art heuristics for the resource constrained project scheduling problem. European Journal of Operational Research 127, 394-407.
• 9. Kolish, R. and Sprecher, A. (1996) PSPLIB A project scheduling library. European Journal of Operational Research 96, 205-216.
• 10. Kolish, R. and Hartmann, S. (2006) Experimental investigation of heuris- tics for resource-constrained project scheduling: An update. European Journal of Operational Research 174, 23–37.
• 11. Mingozzi, A., Maniezzo, V., Ricciardelli, S. and Bianco, L. (1998) An exact algorithm for the resource constrained project scheduling problem based on a new mathematical formulation. Management Science 44, 714–729.
• 12. Rand, G.K. (2000) Critical chain: the Theory of Constraints applied project management. International Journal of Project Management 18 (3), 173–177.
• 13. Tukel, O.I., Rom, W.O. and Eksioglu, S.D. (2006) An investigation of buffer sizing techniques in critical chain scheduling. European Journal of Operational Research 172, 401–416.