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

Science & Mathematics Published 2021 Verification Pending

Overview & Synopsis

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.

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Document Information

Document Title A Genetic Algorithm for a capacitated lot-sizing problem with lost sales, overtimes, and safety stock constraints
Author / Organization Benoît Le Badezet, François Larroche, Odile Bellenguez, Guillaume Massonnet
Subject & Discipline Multidisciplinary Academic Open Research
Categories Science & Mathematics
Publication Year 2021
License / Rights Open Access / Creative Commons
Resource Verification Listed PDF (Verification Pending)
Original Host Website HAL Open Science (hal.science)
File Format application/pdf (Portable Document Format)
Language EN
Catalog ID DOC-221174
Original Source Link Visit Source Page on hal.science »