Global Propagation of Transition Cost for Fixed Job Scheduling

Ruixin Wang (1) , Nicolas Barnier (2)

1 CAUC-ENAC - Joint Research Center of Applied Mathematics for ATM
2 ENAC - Ecole Nationale de l'Aviation Civile

We present a new Constraint Programming (CP) model to optimize the transition cost of Fixed Job Scheduling (FJS), which improves our previous approach based on per-resource constraints by orders of magnitude. Our new model relies on a much tighter relaxation which encompasses all resources to directly propagate on the global cost, thanks to the MinWeightAllDiff optimization constraint. We also present several strategies which exploit the optimal matching computed by the MinWeightAllDiff constraint to efficiently guide the search. The resulting CP solver, using parallel cooperation between the strategies, consistently outperforms a state-of-the-art MIP solver on real instances of an FJS application, the Gate Allocation Problem, at Paris-Charles-de-Gaulle international airport.

Domaines: Optimisation et contrôle [math.OC]

Ruixin Wang, Nicolas Barnier. Global Propagation of Transition Cost for Fixed Job Scheduling. ECAI 2020, 24th European Conference on Artificial Intelligence, Aug 2020, Santiago de Compostela, Spain. ⟨hal-02935488⟩