Automation and Remote Control

, Volume 62, Issue 8, pp 1366–1375 | Cite as

Algorithms of Optimal Supply of Resources to a Group of Projects (Stochastic Networks)

  • D. I. Golenko-Ginzburg
  • S. M. Lyubkin
  • V. S. Rezer
  • S. L. Sitnyakovskii


Several concurrently realized PERT-like network projects with random lengths of the their activities were considered. Each activity consumes several kinds of resources of fixed powers, all resources being reproducible in the course of their service. For each project, the schedule date and the admissible confidence probability of timely completion of the project were defined. The initial instants of realization of all projects, the required total power of each of the reproducible resources (for each project), the delivery schedule of rare reproducible resources that are not at the disposal of the project management system, and the schedule of beginning all activities (for each project) were determined. The minimal nonoperational costs (penalty provisions for failure to execute the project in time, fines for idling of the rare external resources, costs of resource lease, et al.,) were used as the target function.


System Theory Timely Completion Project Management Total Power Target Function 
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.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Kolish, R., Project Scheduling Under Resource Constraints, New York: Phisica, 1995.Google Scholar
  2. 2.
    Shtub, A., Bard, J., and Globerson, S., Project Management: Engineering, Technology, and Implementation, New York: Prentice-Hall, 1994.Google Scholar
  3. 3.
    Zhan, J., Heuristics for Scheduling Resource-Constrained Projects in MPM Networks, Eur. J. Oper. Res., 1994, vol. 76 (1), pp. 192-205.Google Scholar
  4. 4.
    Golenko-Ginzburg, D. and Gonik, A., Job-Shop Resource Scheduling via Simulating Random Operations, J. Math. Comput. Simulat., 1997, vol. 44, pp. 427-440.Google Scholar
  5. 5.
    Golenko-Ginzburg, D. and Gonik, A., Stochastic Network Project Scheduling with Nonconsumable Limited Resources, Int. J. Prod. Econ., 1997, vol. 48, pp. 29-37.Google Scholar
  6. 6.
    Golenko-Ginzburg, D. and Gonik, A., A Heuristic for Network Project Scheduling with Random Activity Durations Depending on the Resource Reallocation, Int. J. Prod. Econ., 1998, vol. 55, pp. 149-162.Google Scholar
  7. 7.
    Gonik, A., Resource Scheduling Model with Cost Objectives for Stochastic Network Projects, Commun. Dependability Quality Manag., 1999, vol. 2, no. 1, pp. 102-108.Google Scholar
  8. 8.
    Voropajev, V., Ljubkin, S., Golenko-Ginzburg, D., and Gonik, A., A Model for Supplying with Constrained Resources in Project Management under Random Disturbances, Project Manag., 1999, vol. 5, no. 1, pp. 68-73.Google Scholar

Copyright information

© MAIK “Nauka/Interperiodica” 2001

Authors and Affiliations

  • D. I. Golenko-Ginzburg
    • 1
  • S. M. Lyubkin
    • 2
  • V. S. Rezer
    • 2
  • S. L. Sitnyakovskii
    • 1
  1. 1.Ben-Gurion University of the NegevBeer-ShevaIsrael
  2. 2.SOVNET Project Management AssociationMoscowRussia

Personalised recommendations