Combined Heuristic Approach to Resource-Constrained Project Scheduling Problem

  • Miloš Šeda
  • Radomil Matoušek
  • Pavel Ošmera
  • Čeněk Šandera
  • Roman Weisser
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 68)


This chapter deals with the resource-constrained project scheduling problem that belongs to NP-hard optimisation problems. There are many different heuristic strategies how to shift activities in time when resource requirements exceed their available amounts. We propose a transformation of the problem to a sequence of simpler instances of (multi)knapsack problems that do not use traditionally predefined activity priorities and enable to maximise limited resources in all time intervals given by start or end of an activity and therefore to reduce the total time.


Schedule Problem Simulated Annealing Knapsack Problem Network Graph Starting Vertex 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. 1.
    J. Blazewicz, K.H. Ecker, G. Schmidt, J. Weglarz, Scheduling Computer and Manufacturing Processes (Springer-Verlag, Berlin, 1996)zbMATHGoogle Scholar
  2. 2.
    S.E. Elmaghraby, Activity Networks: Project Planning and Control by Network Models (Wiley, New York, 1977)zbMATHGoogle Scholar
  3. 3.
    P. Brucker, A. Drexl, R. Möhring, K. Neumann, E. Pesch, Resource-constrained project scheduling: notation, classification, models, and methods. Eur. J. Oper. Res. 112: 3–41 (1999)zbMATHCrossRefGoogle Scholar
  4. 4.
    W. Herroelen, E. Demeulemeester, B.D. Reyck, A note on the paper “resource-constrained project scheduling: notation, classification, models, and methods” by Brucker et al. Eur. J. Oper. Res. 128, 679–688 (2001)zbMATHCrossRefGoogle Scholar
  5. 5.
    K. Bouleimen, H. Lecocq, A new efficient simulated annealing algorithm for the resource-constrained project scheduling problem and its multiple mode version. Eur. J. Oper. Res. 149, 268–281 (2003)MathSciNetzbMATHCrossRefGoogle Scholar
  6. 6.
    M. Mika, G. Waligóra, J. Weglarz, Simulated annealing and tabu search for multi-mode resource-constrained project scheduling with positive discounted cash flows and different payment models. Eur. J. Oper. Res. 164, 639–668 (2005)zbMATHCrossRefGoogle Scholar
  7. 7.
    A. Azaron, C. Perkgoz, M. Sakawa, A genetic algorithm for the time-cost trade-off in PERT networks. Appl. Math. Comput. 168, 1317–1339 (2005)MathSciNetzbMATHCrossRefGoogle Scholar
  8. 8.
    K.W. Kim, M. Gen, G. Yamazaki, Hybrid genetic algorithm with fuzzy logic for resource-constrained project scheduling. Appl. Soft Comput. 2/3F, 174–188 (2003)CrossRefGoogle Scholar
  9. 9.
    K.W. Kim, Y.S. Yun, J.M. Yoon, M. Gen, G. Yamazaki, Hybrid genetic algorithm with adaptive abilities for resource-constrained multiple project scheduling. Comput. Indus. 56, 143–160 (2005)CrossRefGoogle Scholar
  10. 10.
    C. Artigues, P. Michelon, S. Reusser, Insertion techniques for static and dynamic resource-constrained project scheduling. Eur. J. Oper. Res. 149, 249–267 (2003)MathSciNetzbMATHCrossRefGoogle Scholar
  11. 11.
    V. Valls, S. Quintanilla, F. Ballestin, Resource-constrained project scheduling: a critical activity reordering heuristic. Eur. J. Oper. Res. 149, 282–301 (2003)MathSciNetzbMATHCrossRefGoogle Scholar
  12. 12.
    L.-Y. Tseng, S.-C. Chen, A hybrid metaheuristic for the resource-constrained project scheduling problem. Eur. J. Oper. Res. 175(2), 707–721 (2006)Google Scholar
  13. 13.
    H. Zhang, X. Li, H. Li, F. Huang, Particle swarm optimization-based schemes for resource-constrained project scheduling. Autom. Constr. 14, 393–404 (2005)CrossRefGoogle Scholar
  14. 14.
    T.H. Cormen, C.E. Leiserson, R.L. Rivest, C. Stein, Introduction to Algorithms (MIT Press, Cambridge, MA, 2001)zbMATHGoogle Scholar
  15. 15.
    J. Klapka, J. Dvořák, P. Popela, Methods of Operational Research (in Czech) (VUTIUM, Brno, 2001)Google Scholar
  16. 16.
    C.R. Reeves, Modern Heuristic Techniques for Combinatorial Problems (Blackwell Scientific Publications, Oxford, 1993)zbMATHGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2010

Authors and Affiliations

  • Miloš Šeda
    • 1
  • Radomil Matoušek
  • Pavel Ošmera
  • Čeněk Šandera
  • Roman Weisser
  1. 1.Institute of Automation and Computer Science, Faculty of Mechanical EngineeringBrno University of TechnologyBrnoCzech Republic

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