Matheuristics to optimize refueling and maintenance planning of nuclear power plants

Nicolas Dupin () and El-Ghazali Talbi ()
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Nicolas Dupin: Université Paris-Saclay, CNRS, Laboratoire de recherche en informatique
El-Ghazali Talbi: Univ. Lille

Journal of Heuristics, 2021, vol. 27, issue 1, No 4, 63-105

Abstract: Abstract Planning the maintenance of nuclear power plants is a complex optimization problem, involving a joint optimization of maintenance dates, fuel constraints and power production decisions. This paper investigates Mixed Integer Linear Programming (MILP) matheuristics for this problem, to tackle large size instances used in operations with a time scope of 5 years, and few restrictions with time window constraints for the latest maintenance operations. Several constructive matheuristics and a Variable Neighborhood Descent local search are designed. The matheuristics are shown to be accurately effective for medium and large size instances. The matheuristics give also results on the design of MILP formulations and neighborhoods for the problem. Contributions for the operational applications are also discussed. It is shown that the restriction of time windows, which was used to ease computations, induces large over-costs and that this restriction is not required anymore with the capabilities of matheuristics or local searches to solve such size of instances. Our matheuristics can be extended to a bi-objective optimization extension with stability costs, for the monthly re-optimization of the maintenance planning in the real-life application.

Keywords: Hybrid heuristics; Matheuristics; Mixed integer programming; Maintenance planning; Nuclear power plants; Optimization in energy (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (4)

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DOI: 10.1007/s10732-020-09450-0

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