Interval-Based Language for Modeling Scheduling Problems: An Extension to Constraint Programming

IBM ILOG CP Optimizer (CPO) provides a scheduling language supported by a robust and efficient automatic search. This paper summes up the major language constructs and shed some lights on their propagations. Among the main constructs it introduces the notion of interval variable which enable reasoning on conditional time-intervals representing activities or tasks that may or may not be executed in the final schedule. In Constraint-Based Scheduling, those problems are usually handled by defining new global constraints over classical integer variables. This dual perspective facilitates an easy modeling process while ensuring a strong constraint propagation and an efficient search in the engine. The approach forms the foundations of the new generation of scheduling model and algorithms provided in CPO. Small examples are provided at the end of the language construct, however at the end of the paper three larger/real life examples recently studied in the scheduling literature are presented along some computational results illustrating both the expressivity of the modeling language and the robustness of the automatic search. Interestingly all three problems can easily be modeled with the language in only a few dozen lines (the complete models are provided) and on average the automatic search outperforms existing problem specific approaches.