Abstract
With the development of project scheduling models and methods arose the need for data instances in order to benchmark the solution procedures. Generally, benchmark instances can be distinguished by their origin into real world problems and artificial problems. The analysis of algorithmic performance on real world problem instances is of a high practical relevance, but at the same time it is only an analysis of individual cases. Consequently, general conclusions about the algorithms cannot be drawn. A solution procedure which shows very good performance on one real world instance might produce poor results on another. In order to allow a systematic evaluation of the performance of algorithms, characteristics of the projects have to be identified. The characteristics can then serve as the parameters for the systematic generation of artificial instances. The variation of the levels of these problem parameters in a full factorial design study allows to produce a set of well-balanced instances (cf. Montgomery 1976).
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References
Agrawal, M.K., Elmaghraby, S.E., and W. Herroelen 1996. Dagen: A generator of testsets for project activity nets. European Journal of Operational Research, 90, 376–382.
Alvarez-Valdés, R. and J.M. Tamarit 1989. Heuristic algorithms for resource-constrained project scheduling: A review and an empirical analysis. Advances in project scheduling. 113–134, Słowiński, R. and J. Węglarz (eds.). Elsevier, Amsterdam.
Bartusch, M., Möhring, R.H., and F.J. Radermacher 1988. Scheduling project networks with resource constraints and time windows. Annals of Operations Research, 16, 201–240.
Becker, P. 1996. An embeddable and extendable language for large-scale programming on the Internet. Proceedings of the 16-th International Conference on Distributed Computing Systems (ICDCS’96).
Bein, W.W., Kamburowski, J., and M.F.M. Stallmann 1992. Optimal reduction of two-terminal directed graphs. SIAM Journal on Computing, 221, 6, 1112–1129.
Boctor, F. 1993. Heuristics for scheduling projects with resource restrictions and several resource duration modes. International Journal of Production Research, 31, 11, 2547–2558.
Brucker, P., Knust, S., Schoo, A., and O. Thiele 1998. A branch & bound algorithm for the resource-constrained project scheduling problem. European Journal of Operational Research, forthcoming.
Davis, E.W. 1969. An exact algorithm for the multiple constrained project scheduling problem. PhD thesis, Yale University.
Demeulemebster, E., Dodin, B., and W. Herroelen 1993. A random activity network generator. Operations Research, 41, 972–980.
Dembulemeester, E. and W. Herroelen 1997. New benchmark results for the resource-constrained project scheduling problem. Management Science, 43, 11, 1485–1492.
De Reyck, R. and W. Herroelen 1996. A Branch-and Bound Procedure for the Resource-Constrained Project Scheduling Problem with Generalized Precedence Relations. Technical Report 9613, Operations Management Group, Department of Applied Economics, Katholieke Universiteit Leuven.
Drexl, A., Juretzka, J., Salewski, F., and A. Schirmer 1998. New modeling concepts and their impact on resource-constrained project scheduling. Handbook on recent advances in project scheduling. Chapter 18, Weglarz, J. (ed.). Kluwer, Dordrecht.
Drexl, A., Nissen, R., Patterson, J.H., and F. Salewski 1997. Pro-Gen/πx —bAn instance generator for resource-constrained project schedul-ing problems with partially renewable resources and further extensions Technical Report, Institut für Betriebswirtschaftslehre, Universität Kiel.
Franck, B. and K. Neumann 1997. Resource-constrained project scheduling with time windows — structural questions and priority-rule methods. Technical Report 492, Institut für Wirtschaftstheorie und Operations Research, Universität Karlsruhe.
GüNther, O., Müller, R., Schmidt, P., Bhargava, H.K., And R. Kr-Ishnan 1997. Mmm: A Web-based system for sharing statistical computing modules. IEEE Internet Computing, 3, 1, 59–68.
Hartmann, S. 1997 Project scheduling with multiple modes: A genetic algorithm. Technical Report 435, Manuskripte aus den Instituten für Betriebswirtschaftslehre der Universität Kiel.
Hartmann, S. and A. Drexl 1997. Project scheduling with multiple modes: A comparison of exact algorithms. Technical Report 430, Manuskripte aus den Instituten für Betriebswirtschaftslehre der Universität Kiel.
Herroelen, W., Demeulemeester, E., and B. De Reyck 1997. Project network models with discounted cash flows: A guided tour through recent developments. European Journal of Operational Research, 100, 1, 97–121.
Heilmann, R. 1998. A branch-and-bound procedure for the MRCPSP/max. Technical Report 512, Institut für Wirtschaftstheorie und Operations Research, Universität Karlsruhe.
Kolisch, R. and S. Hartmann 1998. Heuristic algorithms for the resource constrained project scheduling problem: Classification and Computational Analysis. Handbook on recent advances in project scheduling. Chapter 7, Weglarz, J. (ed.). Kluwer, Dordrecht.
Kolisch, R. and R. Padman 1997. An integrated survey of project scheduling. Technical Report 463, Manuskripte aus den Instituten für Betriebswirtschaftslehre der Universität Kiel.
Kolisch, R. 1996. Efficient priority rules for the resource-constrained project scheduling problem. Journal of Operations Management, 14, 3, 179–192.
Kolisch, R. and A. Sprecher 1996. PSPLIB — a project scheduling problem library. European Journal of Operational Research, 96, 205–216.
Kolisch, R., Sprecher, A., And A. Drexl 1995. Characterization and generation of a general class of resource-constrained project scheduling problems.Management Science, 41, 10, 1693–1703.
Mingozzi, A., Maniezzo, V., Ricciardelli, S., and L. Bianco 1998. An exact algorithm for project scheduling with resource constraints based on a new mathematical formulation. Management Science, forthcoming.
Montgomery, D.C. 1976. Design and analysis of experiments. Wiley, New York.
Neumann, K. and J. Zimmermann 1997. Resource-levelling for projects with schedule-dependent time windows, Technical Report 508, Institut für Wirt-schaftstheorie und Operations Research, Universität Karlsruhe.
Nübel, H. 1998 A branch-and-bound procedure for the resource investment problem with generalized precedence constraints. Technical Report 516, Institut für Wirtschaftstheorie und Operations Research, Universität Karlsruhe.
Patterson, J.H. 1984. A comparison of exact approaches for solving the multiple constrained resource, project scheduling problem. Management Science, 30, 7, 854–867.
Patterson, J.H. and W.D. Huber 1974. A horizon-varying, zero-one approach to project scheduling. Management Science, 20, 990–998.
Schwindt, C. 1997. Verfahren zur Lösung des ressourcenbeschränkten Projekt-dauerminimierungsproblems mit planungsabhängigen Zeitfenstern. Doctoral Dissertation, Universität Karlsruhe.
Schwindt, C. 1996. Generation of resource-constrained project scheduling problems with minimal and maximal time lags. Technical Report 489, Institut fur Wirtschaftstheorie und Operations Research, Universität Karlsruhe.
Sprecher, A. 1996. Scheduling resource constrained projects competitively at modest memory requirements. Technical Report 425, Manuskripte aus den Instituten für Betriebswirtschaftslehre der Universität Kiel.
Sprecher, A. and A. Drexl 1996a. Solving multi-mode resource-constrained project scheduling by a simple, general, and powerful sequencing algorithm. Part I: Theory. Technical Report 385, Manuskripte aus den Instituten für Betriebswirtschaftslehre der Universität Kiel.
Sprecher, A. and A. Drexl 1996b. Solving multi-mode resource-constrained project scheduling problems by a simple, general, and powerful sequencing algorithm. Part II: Computation. Technical Report 386, Manuskripte aus den Instituten für Betriebswirtschaftslehre der Universität Kiel.
Talbot, F.B. and J.H. Patterson 1978. An efficient integer programming algorithm with network cuts for solving resource-constrained scheduling problems. Management Science, 24, 11, 1163–1174.
Thesen, A. 1977. Measures of the restrictiveness of project networks. Networks, 7, 193–208.
Tsubakitani, S. and R.F. Deckro 1990. A heuristic for multi-project scheduling with limited resources in the housing industry. European Journal of Operational Research, 49, 80–91.
Valadares Tavares, L. 1986. Multicriteria scheduling of a railway renewal program. European Journal of Operational Research, 25, 395–405.
Zimmermann, J. 1997. Heuristics for resource-levelling problems in project scheduling with minimum and maximum time lags, Technical Report 491, Institut für Wirischaftstheorie und Operations Research, Universität Karlsruhe.
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Kolisch, R., Schwindt, C., Sprecher, A. (1999). Benchmark Instances for Project Scheduling Problems. In: Węglarz, J. (eds) Project Scheduling. International Series in Operations Research & Management Science, vol 14. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-5533-9_9
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DOI: https://doi.org/10.1007/978-1-4615-5533-9_9
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