LEFEBVRE, Henri; CLAUTIAUX, François; DETIENNE, Boris

doi:10.1007/s10951-022-00775-1

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LEFEBVRE, Henri
Alma Mater Studiorum Università di Bologna = University of Bologna [UNIBO]

CLAUTIAUX, François
Institut de Mathématiques de Bordeaux [IMB]
Reformulations based algorithms for Combinatorial Optimization [Realopt]
Formulations étendues et méthodes de décomposition pour des problèmes génériques d'optimisation [EDGE]

DETIENNE, Boris
Institut de Mathématiques de Bordeaux [IMB]
Reformulations based algorithms for Combinatorial Optimization [Realopt]
Formulations étendues et méthodes de décomposition pour des problèmes génériques d'optimisation [EDGE]

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Journal of Scheduling. 2023 n° 26, p. 169-191

Springer Verlag

Fecha de defensa

2023

Resumen en inglés

Minimizing the weighted number of tardy jobs {on one machine} is a classical and intensively studied scheduling problem. In this paper, we develop a two-stage robust approach, where exact weights are known after accepting to perform the jobs, and before sequencing them on the machine. This assumption allows diverse recourse decisions to be taken in order to better adapt one's mid-term plan.The contribution of this paper is twofold: first, we introduce a new scheduling problem and model it as a min-max-min optimization problem with mixed-integer recourse by extending existing models proposed for the deterministic case. Second, we take advantage of the special structure of the problem to propose twosolution approaches based on results from the recent robust optimization literature: namely the finite adaptability (Bertsimas and Caramanis, 2010) and a convexification-based approach (Arslan and Detienne, 2022). We also study the additional cost of the solutions if the sequenceof jobs has to be decided before the uncertainty is revealed.Computational experiments are reported to analyze the effectiveness of our approaches.< Leer menos

Palabras clave en inglés

One-machine scheduling

Robust optimization

Two-stage optimization

Mixed-integer recourse

Exact approach

Integer programming

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A two-stage robust approach for {minimizing} the weighted number of tardy jobs with objective uncertainty

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