A Genetic Algorithm for a capacitated lot-sizing problem with lost sales, overtimes, and safety stock constraints

Benoît Le Badezet (1) , François Larroche (2, 3) , Odile Bellenguez (2, 3) , Guillaume Massonnet (2, 3)

1 UN - Université de Nantes
2 IMT Atlantique - DAPI - Département Automatique, Productique et Informatique
3 LS2N - équipe SLP - Systèmes Logistiques et de Production

This paper deals with a complex production planning problem with lost sales, overtimes, safety stock and sequence dependent setup times on parallel and unrelated machines. The main challenge of this work is to propose a solution approach to obtain a good feasible plan in a short execution time (around 2 minutes) for large industrial instances. We develop a genetic algorithm that combines several operations already defined in the literature to solve the problem. Preliminary numerical results obtained with our algorithm are presented and compared to a straightforward MIP resolution. The method appears to be an appealing alternative on large instances when the computational time is limited.

Domaines: Informatique [cs]

Benoît Le Badezet, François Larroche, Odile Bellenguez, Guillaume Massonnet. A Genetic Algorithm for a capacitated lot-sizing problem with lost sales, overtimes, and safety stock constraints. 2021. ⟨hal-03365397⟩