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A novel solution approach with ML-based pseudo-cuts for the Flight and Maintenance Planning problem

Peschiera, Franco and Dell, Robert and Royset, Johannes and Haït, Alain and Dupin, Nicolas and Battaïa, Olga A novel solution approach with ML-based pseudo-cuts for the Flight and Maintenance Planning problem. (2020) OR Spectrum. ISSN 0171-6468

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Official URL: https://doi.org/10.1007/s00291-020-00591-z

Abstract

This paper deals with the long-term Military Flight and Maintenance Planning problem. In order to solve this problem efficiently, we propose a new solution approach based on a new Mixed Integer Program and the use of both valid cuts generated on the basis of initial conditions and learned cuts based on the prediction of certain characteristics of optimal or near-optimal solutions. These learned cuts are generated by training a Machine Learning model on the input data and results of 5000 instances. This approach helps to reduce the solution time with little losses in optimality and feasibility in comparison with alternative matheuristic methods. The obtained experimental results show the benefit of a new way of adding learned cuts to problems based on predicting specific characteristics of solutions.

Item Type:Article
Audience (journal):International peer-reviewed journal
Uncontrolled Keywords:
Institution:French research institutions > Centre National de la Recherche Scientifique - CNRS (FRANCE)
Université de Toulouse > Institut Supérieur de l'Aéronautique et de l'Espace - ISAE-SUPAERO (FRANCE)
Other partners > Université Paris-Saclay (FRANCE)
Other partners > CentraleSupélec (FRANCE)
Other partners > KEDGE Business School (FRANCE)
Other partners > Naval Postgraduate School (USA)
Laboratory name:
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Deposited On:13 Jan 2021 14:06

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