ILOG SCHEDULE

Implementation of resource constraints in ILOG SCHEDULE: a library for the development of constraint-based scheduling systems. It has been argued that the use of constraint-based techniques and tools enables the implementation of precise, flexible efficient and extensible scheduling systems; precise and flexible as the system can take into account any constraint expressible in the constraint language; efficient in as much as highly optimised constraint propagation procedures are now available; extensible as the consideration of a new type of constraint may require (especially in an object-oriented framework) only an extension to the constraint system or, in the worst case, the implementation of additional decision-making modules (without needs for modification of the existing code). The paper presents ILOG SCHEDULE, a C++ library enabling the representation of a wide collection of scheduling constraints in terms of ’resources’ and ’activities’. ILOG SCHEDULE is based on SOLVER, the generic software tool for object-oriented constraint programming from ILOG. SOLVER variables and constraints can be accessed from SCHEDULE activities and resources. As a result, SCHEDULE users can make use of SOLVER to represent specific constraints, and implement and combine the specific problem-solving strategies that are the most appropriate for the scheduling application under consideration. It is hoped-and expected-that object-oriented constraint programming tools like SCHEDULE will enable the industry to make decisive steps toward the implementation of ’state-of-the-art’ highly flexible, constraint-based scheduling applications.


References in zbMATH (referenced in 68 articles )

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  1. Abidin Çil, Zeynel; Kizilay, Damla: Constraint programming model for multi-manned assembly line balancing problem (2020)
  2. Bukchin, Yossi; Raviv, Tal; Zaides, Ilya: The consecutive multiprocessor job scheduling problem (2020)
  3. Gerhards, Patrick: The multi-mode resource investment problem: a benchmark library and a computational study of lower and upper bounds (2020)
  4. Hà, Minh Hoàng; Nguyen, Tat Dat; Nguyen Duy, Thinh; Pham, Hoang Giang; Do, Thuy; Rousseau, Louis-Martin: A new constraint programming model and a linear programming-based adaptive large neighborhood search for the vehicle routing problem with synchronization constraints (2020)
  5. Lunardi, Willian T.; Birgin, Ernesto G.; Laborie, Philippe; Ronconi, Débora P.; Voos, Holger: Mixed integer linear programming and constraint programming models for the online printing shop scheduling problem (2020)
  6. Sacramento, David; Solnon, Christine; Pisinger, David: Constraint programming and local search heuristic: a matheuristic approach for routing and scheduling feeder vessels in multi-terminal ports (2020)
  7. van Bulck, David; Goossens, Dries; Schönberger, Jörn; Guajardo, Mario: RobinX: a three-field classification and unified data format for round-robin sports timetabling (2020)
  8. Van Cauwelaert, Sascha; Dejemeppe, Cyrille; Schaus, Pierre: An efficient filtering algorithm for the unary resource constraint with transition times and optional activities (2020)
  9. Osorio-Valenzuela, Luis; Pereira, Jordi; Quezada, Franco; Vásquez, Óscar C.: Minimizing the number of machines with limited workload capacity for scheduling jobs with interval constraints (2019)
  10. Yahouni, Zakaria; Mebarki, Nasser; Sari, Zaki: Evaluation of a new decision-aid parameter for job shop scheduling under uncertainties (2019)
  11. Hooker, J. N.; van Hoeve, W.-J.: Constraint programming and operations research (2018)
  12. Laborie, Philippe; Rogerie, Jérôme; Shaw, Paul; Vilím, Petr: IBM ILOG CP optimizer for scheduling. 20+ years of scheduling with constraints at IBM/ILOG (2018)
  13. Polyakovskiy, Sergey; M’Hallah, Rym: A hybrid feasibility constraints-guided search to the two-dimensional bin packing problem with due dates (2018)
  14. Cappart, Quentin; Schaus, Pierre: Rescheduling railway traffic on real time situations using time-interval variables (2017)
  15. Kreter, Stefan; Schutt, Andreas; Stuckey, Peter J.: Using constraint programming for solving RCPSP/MAX-cal (2017)
  16. Talbi, El-Ghazali: Combining metaheuristics with mathematical programming, constraint programming and machine learning (2016)
  17. Goel, V.; Slusky, M.; van Hoeve, W.-J.; Furman, K. C.; Shao, Y.: Constraint programming for LNG ship scheduling and inventory management (2015)
  18. Grimes, Diarmuid; Hebrard, Emmanuel: Solving variants of the job shop scheduling problem through conflict-directed search (2015)
  19. Shirzadeh Chaleshtarti, A.; Shadrokh, S.; Fathi, Y.: Branch and bound algorithms for resource constrained project scheduling problem subject to nonrenewable resources with prescheduled procurement (2014)
  20. Schutt, Andreas; Feydy, Thibaut; Stuckey, Peter J.; Wallace, Mark G.: Solving RCPSP/max by lazy clause generation (2013)

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