A constraint programming-based approach to a large-scale energy management problem with varied constraints

Authors:
Felix Brandt;Reinhard Bauer;Markus Völker;Andreas Cardeneo
Affiliations:
Logistics Systems Engineering, Research Center for Information Technology, Karlsruhe, Germany 76131;Institute of Theoretical Informatics, Karlsruhe Institute of Technology, Karlsruhe, Germany 76128;Institute of Theoretical Informatics, Karlsruhe Institute of Technology, Karlsruhe, Germany 76128;Logistics Systems Engineering, Research Center for Information Technology, Karlsruhe, Germany 76131
Venue:
Journal of Scheduling
Year:
2013

Citing 2
Cited 1

Local search for mixed-integer nonlinear optimization: a methodology and an application

EvoCOP'11 Proceedings of the 11th European conference on Evolutionary computation in combinatorial optimization
When constraint programming and local search solve the scheduling problem of electricité de france nuclear power plant outages

CP'06 Proceedings of the 12th international conference on Principles and Practice of Constraint Programming

A 0---1 integer linear programming approach to schedule outages of nuclear power plants

Journal of Scheduling

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper addresses a large-scale power plant maintenance scheduling and production planning problem, which has been proposed by the ROADEF/EURO Challenge 2010. We develop two lower bounds for the problem: a greedy heuristic and a flow network for which a minimum cost flow problem has to be solved.Furthermore, we present a solution approach that combines a constraint programming formulation of the problem with several heuristics. The problem is decomposed into an outage scheduling and a production planning phase. The first phase is solved by a constraint program, which additionally ensures the feasibility of the remaining problem. In the second phase we utilize a greedy heuristic--developed from our greedy lower bound--to assign production levels and refueling amounts for a given outage schedule. All proposed strategies are shown to be competitive in an experimental evaluation.