Machine Learning-Guided Dual Heuristics and New Lower Bounds for the Refueling and Maintenance Planning Problem of Nuclear Power Plants

Machine Learning-Guided Dual Heuristics and New Lower Bounds for the Refueling and Maintenance Planning Problem of Nuclear Power Plants

This paper studies the hybridization of Mixed Integer Programming (MIP) with dual heuristics and machine learning techniques, to provide dual bounds for a large scale optimization problem from an industrial application. The case study is the EURO/ROADEF Challenge 2010, to optimize the refueling and...

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Bibliographic Details
Main Authors: Nicolas Dupin, El-Ghazali Talbi
Format: Article
Language:English
Published: MDPI AG 2020-07-01
Series:Algorithms
Subjects:
operations research
mixed integer programming
stochastic optimization
dual bounds
dual heuristics
hybrid heuristics
Online Access:https://www.mdpi.com/1999-4893/13/8/185

Internet

https://www.mdpi.com/1999-4893/13/8/185

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