Abstract
The Resource-Constrained Project Scheduling Problem (RCPSP) is a well-known scheduling problem aimed at minimizing the makespan of a project subject to temporal and resource constraints. In this paper we show that hard RCPSPs can be efficiently tackled by a portfolio approach that combines the strengths of different constraint solvers Our approach seeks to predict and run in parallel the best solvers for a new, unseen RCPSP instance by enabling the bound communication between them. This on-average allows to outperform the oracle solver that always chooses the best available solver for any given instance.
Supported by the EU project FP7-644298 HyVar: Scalable Hybrid Variability for Distributed, Evolving Software Systems.
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Notes
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For more details about sunny-cp, we refer the reader to [3].
References
Amadini, R., Gabbrielli, M., Mauro, J.: Portfolio approaches for constraint optimization problems. In: Pardalos, P.M., Resende, M.G.C., Vogiatzis, C., Walteros, J.L. (eds.) LION 2014. LNCS, vol. 8426, pp. 21–35. Springer, Heidelberg (2014). doi:10.1007/978-3-319-09584-4_3
Amadini, R., Gabbrielli, M., Mauro, J.: SUNNY: a Lazy portfolio approach for constraint solving. TPLP 4–5, 509–524 (2014)
Amadini, R., Gabbrielli, M., Mauro, J.: A multicore tool for constraint solving. In: IJCAI, pp. 232–238 (2015)
Amadini, R., Gabbrielli, M., Mauro, J.: SUNNY-CP: a sequential CP portfolio solver. In: SAC, pp. 1861–1867 (2015)
Amadini, R., Gabbrielli, M., Mauro, J.: Why CP portfolio solvers are (under)utilized? Issues and challenges. In: Falaschi, M. (ed.) LOPSTR 2015. LNCS, vol. 9527, pp. 349–364. Springer, Heidelberg (2015). doi:10.1007/978-3-319-27436-2_21
Amadini, R., Stuckey, P.J.: Sequential time splitting and bounds communication for a portfolio of optimization solvers. In: O’Sullivan, B. (ed.) CP 2014. LNCS, vol. 8656, pp. 108–124. Springer, Heidelberg (2014). doi:10.1007/978-3-319-10428-7_11
Arlot, S., Celisse, A.: A survey of cross-validation procedures for model selection. Statist. Surv. 4, 40–79 (2010)
Christopher Beck, J., Davenport, A.J., Sitarski, E.M., Fox, M.S.: Texture-based heuristics for scheduling revisited. In: AAAI, pp. 241–248 (1997)
Blazewicz, J., Lenstra, J.K., Rinnooy Kan, A.H.G.: Scheduling subject to resource constraints: classification and complexity. Discret. Appl. Math. 5(1), 11–24 (1983)
Brucker, P., Drexl, A., Mohring, R.H., Neumann, K., Pesch, E.: Resource-constrained project scheduling: notation, classification, models, and methods. Eur. J. Oper. Res. 1, 3–41 (1999)
Gomes, C.P., Selman, B.: Algorithm portfolios. Artif. Intell. 1–2, 43–62 (2001)
Hartmann, S., Briskorn, D.: A survey of variants and extensions of the resource-constrained project scheduling problem. Eur. J. Oper. Res. 1, 1–14 (2010)
Herroelen, W., De Reyck, B., Demeulemeester, E.: Resource-constrained project scheduling: a survey of recent developments. Comput. OR 4, 279–302 (1998)
Kolisch, R., Hartmann, S.: Experimental investigation of heuristics for resource-constrained project scheduling: an update. Eur. J. Oper. Res. 1, 23–37 (2006)
Kreter, S., Schutt, A., Stuckey, P.J.: Modeling and solving project scheduling with calendars. In: Pesant, G. (ed.) CP 2015. LNCS, vol. 9255, pp. 262–278. Springer, Heidelberg (2015). doi:10.1007/978-3-319-23219-5_19
Nethercote, N., Stuckey, P.J., Becket, R., Brand, S., Duck, G.J., Tack, G.: MiniZinc: towards a standard CP modelling language. In: CP, pp. 529–543 (2007)
Ohrimenko, O., Stuckey, P.J., Michael, C.: Propagation via lazy clause generation. Constraints 3, 357–391 (2009)
Rossi, F., van Beek, P., Walsh, T. (eds.): Handbook of Constraint Programming (2006)
Schutt, A., Feydy, T., Stuckey, P.J., Wallace, M.G.: Explaining the cumulative propagator. Constraints 3, 250–282 (2011)
Schutt, A., Feydy, T., Stuckey, P.J., Wallace, M.G.: Solving RCPSP/max by lazy clause generation. J. Sched. 3, 273–289 (2013)
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Amadini, R., Gabbrielli, M., Mauro, J. (2016). Parallelizing Constraint Solvers for Hard RCPSP Instances. In: Festa, P., Sellmann, M., Vanschoren, J. (eds) Learning and Intelligent Optimization. LION 2016. Lecture Notes in Computer Science(), vol 10079. Springer, Cham. https://doi.org/10.1007/978-3-319-50349-3_16
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