This paper introduces a three-phase heuristic approach for a large-scale energy management and maintenance scheduling problem. The problem is concerned with scheduling maintenance and refueling for nuclear power plants up to five years into the future, while handling a number of scenarios for future demand and prices. The goal is to minimize the expected total production costs. The first phase of the heuristic solves a simplified constraint programming model of the problem, the second performs a local search, and the third handles overproduction in a greedy fashion. This work was initiated in the context of the ROADEF EURO Challenge 2010, a competition organized jointly by the French Operational Research and Decision Support Society, the European Operational Research Society, and the European utility company Electricite de France. In the concluding phase of the competition our team ranked second in the junior category and sixth overall. After correcting an implementation bug in the program that was submitted for evaluation, our heuristic solves all ten real-life instances, and the solutions obtained are all within 2.45 of the currently best known solutions. The results given here would have ranked first in the original competition.
Abstract The problem addressed here is scheduling the shutdown for refueling and maintenance of nuclear power plants. The models have up to four reactors requiring of the order of five shutdowns each over a five-year time horizon. The resulting mixed-integer program is large and complex with interesting structure. We show good results using a mixed-integer optimizer taking advantage of a strong linear programming formulation.