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Erschienen in: Journal of Scheduling 4/2020

15.02.2020

An Efficient Filtering Algorithm for the Unary Resource Constraint with Transition Times and Optional Activities

verfasst von: Sascha Van Cauwelaert, Cyrille Dejemeppe, Pierre Schaus

Erschienen in: Journal of Scheduling | Ausgabe 4/2020

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Abstract

This paper describes a unified global constraint to model scheduling problems with unary resources, i.e., each resource can process only a single activity at a time. In addition, the constraint enforces sequence-dependent transition times between activities. It often happens that activities are grouped into families with zero transition times within a family. Moreover, some of the activities might be optional from the resource viewpoint (typically in the case of alternative resources). The global constraint unifies reasoning with both optional activities and families of activities. The scalable filtering algorithms we discuss keep a low time complexity of \(\mathcal {O}(n \cdot \log (n) \cdot \log (f))\), where n is the number of tasks on the resource and f is the number of families. This results from the fact that we extend the \(\varTheta \)-tree data structure used for the Unary Resource constraint without transition times. Our experiments demonstrate that our global constraint strengthens the pruning of domains as compared with existing approaches, leading to important speedups. Moreover, our low time complexity allows maintaining a small overhead, even for large instances. These conclusions are particularly true when optional activities are present in the problem.

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Fußnoten
1
In this paper we assume without loss of generality that \(p_{i}\) is constant.
 
2
A more general case is when a positive transition \( tt _{f, f}^\mathcal {F}\) must occur between activities of the same family f. In this case, one can fall back to zero transition times within a family, assuming \( tt _{f, f}^\mathcal {F} \le tt _{f', f}^\mathcal {F} \forall f' \in tt ^\mathcal {F}\). One can artificially: (1) increase the duration of activities of the family f with \( tt _{f, f}^\mathcal {F}\); and (2) decrease the transition times from family f by \( tt _{f, f}^\mathcal {F}\). Yet, one cannot always perform this trick, so we keep the hypothesis in the rest of the paper that \( tt _{f, f}^\mathcal {F} = 0\).
 
3
The approach of Grimes and Hebrard (2010) does not actually use a precedence graph structure explicitly, but reifies the precedence constraints and branches on the associated boolean variables.
 
4
Practical implementations apply the symmetric rules by applying the original rules on mirrors of the original activities. The mirror activity m of an activity i is modeled with the variables \(s_{m} = - c_{i}\), \(c_{m} = - s_{i}\) and \(p_{m} = p_{i}\).
 
5
Alternatively, as proposed in Vilım (2009a, b) in the case of the Edge-Finding algorithm, one could consider all activities of \(T\) and pretend the latest start time of optional activities amounts to \(+\infty \). All activities (including optionals) are then inserted in Q and the rest of the algorithm remains unchanged.
 
6
Or as for the Detectable Precedence algorithm, one can pretend the latest start time of optional activities amounts to \(+\infty \) and insert all of them in Q.
 
7
Notice that this is equivalent to what is proposed in Vilım (2009a, b). The author suggests handling optional activities by modifying the input data rather than the algorithm: \( lct _{o}\) is assumed to be \(+\infty \) for all optional activities \(o \in O\).
 
8
Some processors also have a dedicated machine instruction.
 
9
The approach can also be used for sets of activities. The description focuses here on families since it was initially used in the context of family-based transition times.
 
10
Typically maximum 10.
 
13
Still, if it is available at a low cost, it can be beneficial to use it.
 
Literatur
Zurück zum Zitat Allahverdi, A., Ng, C., Cheng, T. E., & Kovalyov, M. Y. (2008). A survey of scheduling problems with setup times or costs. European Journal of Operational Research, 187(3), 985–1032.CrossRef Allahverdi, A., Ng, C., Cheng, T. E., & Kovalyov, M. Y. (2008). A survey of scheduling problems with setup times or costs. European Journal of Operational Research, 187(3), 985–1032.CrossRef
Zurück zum Zitat Artigues, C., Belmokhtar, S., & Feillet, D. (2004). A new exact solution algorithm for the job shop problem with sequence-dependent setup times. In J. C. Régin, & M. Rueher (Eds.), Integration of AI and OR techniques in constraint programming for combinatorial optimization problems (pp. 37–49). Springer. Artigues, C., Belmokhtar, S., & Feillet, D. (2004). A new exact solution algorithm for the job shop problem with sequence-dependent setup times. In J. C. Régin, & M. Rueher (Eds.), Integration of AI and OR techniques in constraint programming for combinatorial optimization problems (pp. 37–49). Springer.
Zurück zum Zitat Artigues, C., & Feillet, D. (2008). A branch and bound method for the job-shop problem with sequence-dependent setup times. Annals of Operations Research, 159(1), 135–159.CrossRef Artigues, C., & Feillet, D. (2008). A branch and bound method for the job-shop problem with sequence-dependent setup times. Annals of Operations Research, 159(1), 135–159.CrossRef
Zurück zum Zitat Baptiste, P., Laborie, P., Le Pape, C., & Nuijten, W. (2006). Constraint-based scheduling and planning. In F. Rossi, P. van Beek, & T. Walsh (Eds.), Handbook of constraint programming, Chap. 22 (pp. 759–797). Amsterdam: Elsevier. Baptiste, P., Laborie, P., Le Pape, C., & Nuijten, W. (2006). Constraint-based scheduling and planning. In F. Rossi, P. van Beek, & T. Walsh (Eds.), Handbook of constraint programming, Chap. 22 (pp. 759–797). Amsterdam: Elsevier.
Zurück zum Zitat Baptiste, P., Le Pape, C., & Nuijten, W. (2001). Constraint-based scheduling: Applying constraint programming to scheduling problems, International Series in Operations Research & Management Science (Vol. 39). Berlin: Springer.CrossRef Baptiste, P., Le Pape, C., & Nuijten, W. (2001). Constraint-based scheduling: Applying constraint programming to scheduling problems, International Series in Operations Research & Management Science (Vol. 39). Berlin: Springer.CrossRef
Zurück zum Zitat Barták, R. (2008). Search strategies for scheduling problems with optional activities. In Proceedings of CSCLP 2008 annual ERCIM workshop on constraint solving and constraint logic programming, Rome. Barták, R. (2008). Search strategies for scheduling problems with optional activities. In Proceedings of CSCLP 2008 annual ERCIM workshop on constraint solving and constraint logic programming, Rome.
Zurück zum Zitat Barták, R., & Čepek, O. (2010). Incremental propagation rules for a precedence graph with optional activities and time windows. Transactions of the Institute of Measurement and Control, 32(1), 73–96.CrossRef Barták, R., & Čepek, O. (2010). Incremental propagation rules for a precedence graph with optional activities and time windows. Transactions of the Institute of Measurement and Control, 32(1), 73–96.CrossRef
Zurück zum Zitat Bellman, R. (1956). On a routing problem. DTIC Document: Technical report. Bellman, R. (1956). On a routing problem. DTIC Document: Technical report.
Zurück zum Zitat Brucker, P. (1999). Complex scheduling problems. Zeitschrift Operations Research. 30, 99. Brucker, P. (1999). Complex scheduling problems. Zeitschrift Operations Research. 30, 99.
Zurück zum Zitat Brucker, P., & Thiele, O. (1996). A branch & bound method for the general-shop problem with sequence dependent setup-times. Operations-Research-Spektrum, 18(3), 145–161.CrossRef Brucker, P., & Thiele, O. (1996). A branch & bound method for the general-shop problem with sequence dependent setup-times. Operations-Research-Spektrum, 18(3), 145–161.CrossRef
Zurück zum Zitat Cappart, Q., Thomas, C., Schaus, P., & Rousseau, L. M. (2018). A constraint programming approach for solving patient transportation problems. In International conference on principles and practice of constraint programming (pp. 490–506). Springer. Cappart, Q., Thomas, C., Schaus, P., & Rousseau, L. M. (2018). A constraint programming approach for solving patient transportation problems. In International conference on principles and practice of constraint programming (pp. 490–506). Springer.
Zurück zum Zitat Christofides, N., Mingozzi, A., & Toth, P. (1981). State-space relaxation procedures for the computation of bounds to routing problems. Networks, 11(2), 145–164.CrossRef Christofides, N., Mingozzi, A., & Toth, P. (1981). State-space relaxation procedures for the computation of bounds to routing problems. Networks, 11(2), 145–164.CrossRef
Zurück zum Zitat Dejemeppe, C. (2016). Constraint programming algorithms and models for scheduling applications. Ph.D. thesis, Université catholique de Louvain, Louvain-la-Neuve Dejemeppe, C. (2016). Constraint programming algorithms and models for scheduling applications. Ph.D. thesis, Université catholique de Louvain, Louvain-la-Neuve
Zurück zum Zitat Dejemeppe, C., Van Cauwelaert, S., & Schaus, P. (2015). The unary resource with transition times. In International conference on principles and practice of constraint programming (pp. 89–104). Springer Dejemeppe, C., Van Cauwelaert, S., & Schaus, P. (2015). The unary resource with transition times. In International conference on principles and practice of constraint programming (pp. 89–104). Springer
Zurück zum Zitat Dolan, E. D., & Moré, J. J. (2002). Benchmarking optimization software with performance profiles. Mathematical programming, 91(2), 201–213.CrossRef Dolan, E. D., & Moré, J. J. (2002). Benchmarking optimization software with performance profiles. Mathematical programming, 91(2), 201–213.CrossRef
Zurück zum Zitat Focacci, F., Laborie, P., & Nuijten, W. (2000). Solving scheduling problems with setup times and alternative resources. In AIPS (pp. 92–101). Focacci, F., Laborie, P., & Nuijten, W. (2000). Solving scheduling problems with setup times and alternative resources. In AIPS (pp. 92–101).
Zurück zum Zitat Gay, S., Hartert, R., Lecoutre, C., & Schaus, P.(2015). Conflict ordering search for scheduling problems. In International conference on principles and practice of constraint programming (pp. 140–148). Springer. Gay, S., Hartert, R., Lecoutre, C., & Schaus, P.(2015). Conflict ordering search for scheduling problems. In International conference on principles and practice of constraint programming (pp. 140–148). Springer.
Zurück zum Zitat Gay, S., Schaus, P., & De Smedt, V. (2014). Continuous casting scheduling with constraint programming. In B. O’Sullivan (Ed.), Principles and practice of constraint programming (pp. 831–845). Springer. Gay, S., Schaus, P., & De Smedt, V. (2014). Continuous casting scheduling with constraint programming. In B. O’Sullivan (Ed.), Principles and practice of constraint programming (pp. 831–845). Springer.
Zurück zum Zitat Grimes, D., & Hebrard, E. (2010). Job shop scheduling with setup times and maximal time-lags: A simple constraint programming approach. In Integration of AI and OR techniques in constraint programming for combinatorial optimization problems (pp. 147–161). Springer. Grimes, D., & Hebrard, E. (2010). Job shop scheduling with setup times and maximal time-lags: A simple constraint programming approach. In Integration of AI and OR techniques in constraint programming for combinatorial optimization problems (pp. 147–161). Springer.
Zurück zum Zitat Kruskal, J. B. (1956). On the shortest spanning subtree of a graph and the traveling salesman problem. Proceedings of the American Mathematical society, 7(1), 48–50.CrossRef Kruskal, J. B. (1956). On the shortest spanning subtree of a graph and the traveling salesman problem. Proceedings of the American Mathematical society, 7(1), 48–50.CrossRef
Zurück zum Zitat Laborie, P. (2018). An update on the comparison of MIP, CP and hybrid approaches for mixed resource allocation and scheduling. In International conference on the integration of constraint programming, artificial intelligence, and operations research (pp. 403–411). Springer. Laborie, P. (2018). An update on the comparison of MIP, CP and hybrid approaches for mixed resource allocation and scheduling. In International conference on the integration of constraint programming, artificial intelligence, and operations research (pp. 403–411). Springer.
Zurück zum Zitat Laborie, P., & Rogerie, J. (2008). Reasoning with conditional time-intervals. In FLAIRS conference (pp. 555–560). Laborie, P., & Rogerie, J. (2008). Reasoning with conditional time-intervals. In FLAIRS conference (pp. 555–560).
Zurück zum Zitat Laborie, P., Rogerie, J., Shaw, P., & Vilím, P. (2018). IBM ILOG CP optimizer for scheduling. Constraints, 23(2), 210–250.CrossRef Laborie, P., Rogerie, J., Shaw, P., & Vilím, P. (2018). IBM ILOG CP optimizer for scheduling. Constraints, 23(2), 210–250.CrossRef
Zurück zum Zitat Moore, E. (1959). The shortest path through a maze. In Proceedings international symposium on switching theory. Moore, E. (1959). The shortest path through a maze. In Proceedings international symposium on switching theory.
Zurück zum Zitat Van Cauwelaert, S., Lombardi, M., & Schaus, P. (2015) Understanding the potential of propagators. In International conference on integration of artificial intelligence (AI) and operations research (OR) techniques in constraint programming (pp. 427–436). Springer. Van Cauwelaert, S., Lombardi, M., & Schaus, P. (2015) Understanding the potential of propagators. In International conference on integration of artificial intelligence (AI) and operations research (OR) techniques in constraint programming (pp. 427–436). Springer.
Zurück zum Zitat Van Cauwelaert, S., Lombardi, M., & Schaus, P. (2016). A visual web tool to perform what-if analysis of optimization approaches. Technical report, UCLouvain. Van Cauwelaert, S., Lombardi, M., & Schaus, P. (2016). A visual web tool to perform what-if analysis of optimization approaches. Technical report, UCLouvain.
Zurück zum Zitat Van Cauwelaert, S., Lombardi, M., & Schaus, P. (2017). How efficient is a global constraint in practice? Constraints, 23, 210–250. Van Cauwelaert, S., Lombardi, M., & Schaus, P. (2017). How efficient is a global constraint in practice? Constraints, 23, 210–250.
Zurück zum Zitat Vilım, P. (2007). Global constraints in scheduling. Ph.D. thesis, Charles University in Prague, Faculty of Mathematics and Physics, Department of Theoretical Computer Science and Mathematical Logic, KTIML MFF, Universita Karlova, Malostranské námestı 2/25, 118 00 Praha 1, Czech Republic. Vilım, P. (2007). Global constraints in scheduling. Ph.D. thesis, Charles University in Prague, Faculty of Mathematics and Physics, Department of Theoretical Computer Science and Mathematical Logic, KTIML MFF, Universita Karlova, Malostranské námestı 2/25, 118 00 Praha 1, Czech Republic.
Zurück zum Zitat Vilım, P. (2009a). Edge finding filtering algorithm for discrete cumulative resources in o (kn log n). In I. P. Gent (Ed.), Principles and practice of constraint programming-CP (Vol. 5732, pp. 802–816). Springer. Vilım, P. (2009a). Edge finding filtering algorithm for discrete cumulative resources in o (kn log n). In I. P. Gent (Ed.), Principles and practice of constraint programming-CP (Vol. 5732, pp. 802–816). Springer.
Zurück zum Zitat Vilím, P. (2009b). Max energy filtering algorithm for discrete cumulative resources. In International conference on AI and OR techniques in constriant programming for combinatorial optimization problems (pp. 294–308). Springer. Vilím, P. (2009b). Max energy filtering algorithm for discrete cumulative resources. In International conference on AI and OR techniques in constriant programming for combinatorial optimization problems (pp. 294–308). Springer.
Zurück zum Zitat Vilım, P., & Barták, R. (2012). Filtering algorithms for batch processing with sequence dependent setup times. In Proceedings of the 6th international conference on AI planning and scheduling, AIPS. Vilım, P., & Barták, R. (2012). Filtering algorithms for batch processing with sequence dependent setup times. In Proceedings of the 6th international conference on AI planning and scheduling, AIPS.
Zurück zum Zitat Warren, H. S. (2013). Hacker’s delight. London: Pearson Education. Warren, H. S. (2013). Hacker’s delight. London: Pearson Education.
Zurück zum Zitat Wolf, A. (2009). Constraint-based task scheduling with sequence dependent setup times, time windows and breaks. GI Jahrestagung, 154, 3205–3219. Wolf, A. (2009). Constraint-based task scheduling with sequence dependent setup times, time windows and breaks. GI Jahrestagung, 154, 3205–3219.
Zurück zum Zitat Zampelli, S., Vergados, Y., Van Schaeren, R., Dullaert, W., & Raa, B. (2013). The berth allocation and quay crane assignment problem using a CP approach. In C. Schulte (Ed.), Principles and practice of constraint programming (pp. 880–896). Springer. Zampelli, S., Vergados, Y., Van Schaeren, R., Dullaert, W., & Raa, B. (2013). The berth allocation and quay crane assignment problem using a CP approach. In C. Schulte (Ed.), Principles and practice of constraint programming (pp. 880–896). Springer.
Metadaten
Titel
An Efficient Filtering Algorithm for the Unary Resource Constraint with Transition Times and Optional Activities
verfasst von
Sascha Van Cauwelaert
Cyrille Dejemeppe
Pierre Schaus
Publikationsdatum
15.02.2020
Verlag
Springer US
Erschienen in
Journal of Scheduling / Ausgabe 4/2020
Print ISSN: 1094-6136
Elektronische ISSN: 1099-1425
DOI
https://doi.org/10.1007/s10951-019-00632-8

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