Abstract
Different approaches to a problem generally produce distinct algorithms that have significantly different performance characteristics in varying problem environments. In most instances, a single algorithm is chosen to be applied throughout the solution process of a given problem, thus losing the opportunity to exploit the desirable features of other methods. An Asynchronous Team (A-Team) is a software organization that facilitates cooperation amongst multiple algorithms so that together they produce better solutions than if they were acting alone. This paper explores the feasibility of applying the A-Team approach to the practical problem of resource-constrained project scheduling with cash flows (RCPSPCF). This problem investigates the scheduling of precedence-related and resource-constrained activities to maximize the Net Present Value of the expenses incurred and payments made over the duration of a project. This is a complex combinatorial optimization problem which precludes the development of optimal schedules for projects of practical size. We embed several simple heuristics for solving the RCPSPCF within the iterative, parallel structure of A-Team which provides a natural framework for distributed problem solving. Preliminary results on several randomly generated project networks show that the combination of multiple, simple heuristics perform very well when compared to many single pass, complex optimization-based heuristics proposed in the literature.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
R. Bey, R.H. Doersch and J.H. Patterson, 1981. The Net Present Value Criterion: Its Impact on Project Scheduling, Project Management Quarterly, Vol. 12, No. 2, 35–45.
T.G. Crainic, M. Toulouse and M. Gendreau, 1993a. A Study of Synchronous Parallelization Strategies for Tabu Search, Publication 934, Centre de Recherche sur les Transports, Universite de Montreal.
T.G. Crainic, M. Toulouse and M. Gendreau, 1993b. Appraisal of Asynchronous Parallelization Approaches for Tabu Search, Publication 935, Centre de Recherche sur les Transports, Universite de Montreal.
W. Crowston, F. Glover, G. Thompson and J. Trawick, 1964. Probabilistic and Parametric Learning Methods for the Job Shop Scheduling Problem, GSIA Working Paper, Carnegie Mellon University.
E.W. Davis and J.H. Patterson, 1975. A Comparison of Heuristic and Optimal Solutions in Resource-Constrained Project Scheduling, Management Science, Vol. 21, No. 8, 944–955.
H. Fisher and G.L. Thompson, 1963. Probabilistic Learning Combinations of Local Job-shop Scheduling Rules, In Industrial Scheduling, Prentice-Hall, Inc., 225–251.
F. Glover, 1977. Heuristics for Integer Programming Using Surrogate Constraints, Decision Sciences, Vol. 8, No. 1, 156–166.
F. Glover, 1990. Tabu Search: A Tutorial, Interfaces, Vol. 20, No. 1, 74–94.
M.R. Garey and D.S. Johnson, 1979. Computers and Intractability: A Guide to the Theory of NP-Completeness, W.H. Freeman and Co., New York.
LS. Kurtulus and E.W. Davis, 1982. Multi-Project Scheduling: Categorization of Heuristic Rules Performance, Management Science, Vol. 28, No. 2, 161–172.
R. Padman, D.E. Smith-Daniels and V.L. Smith-Daniels. Heuristic Scheduling of Resource-Constrained Projects with Cash Flows, forthcoming in Naval Research Logistics.
R. Padman, D.E. Smith-Daniels, 1993. Early-Tardy Cost Trade-Offs in Resource Constrained Projects with Cash Flows: An Optimization-based Approach, European Journal of Operational Research, Vol. 65, 295–311.
R.A. Russell, 1986. A Comparison of Heuristics for Scheduling Projects with Cash Flows and Resource Restrictions, Management Science, Vol. 32, No. 10, 1291–1300.
S.N. Talukdar, 1993. Asynchronous Teams, Fourth Symposium on Expert Systems Applications to Power Systems.
S.N. Talukdar and P.S.de Souza, 1992. Scale Efficient Organizations, Proceedings of the 1992 IEEE International Conference on Systems, Man and Cybernetics, Vol. 2, 1458–1463.
S.N. Talukdar, P.S. de Souza, and S. Murthy, 1993. Designing Organizations for Computer-based Agents, International Journal of Engineering Intelligent Systems for Electrical Engineering and Communications.
D. Zhu and R. Padman, 1995. Neural Networks for Heuristic Selection: An Application in Resource-Constrained Project Scheduling, The Impact of Emerging Technologies on Computer Science and Operations Research, eds. S.G. Nash and A. Sofer, Kluwer Academic Publishers, 297–312.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 1997 Springer Science+Business Media New York
About this chapter
Cite this chapter
Zhu, D., Padman, R. (1997). A Cooperative Multi-Agent Approach to Constrained Project Scheduling. In: Barr, R.S., Helgason, R.V., Kennington, J.L. (eds) Interfaces in Computer Science and Operations Research. Operations Research/Computer Science Interfaces Series, vol 7. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-4102-8_16
Download citation
DOI: https://doi.org/10.1007/978-1-4615-4102-8_16
Publisher Name: Springer, Boston, MA
Print ISBN: 978-1-4613-6837-3
Online ISBN: 978-1-4615-4102-8
eBook Packages: Springer Book Archive