Dynamic Programming Based Metaheuristic for Energy Planning Problems

  • Sophie JacquinEmail author
  • Laetitia Jourdan
  • El-Ghazali Talbi
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8602)


In this article, we propose DYNAMOP (DYNAmic programming using Metaheuristic for Optimization Problems) a new dynamic programming based on genetic algorithm to solve a hydro-scheduling problem. The representation which is based on a path in the graph of states of dynamic programming is adapted to dynamic structure of the problem and it allows to hybridize easily evolutionary algorithms with dynamic programming. DYNAMOP is tested on two case studies of hydro-scheduling problem with different price scenarios. Experiments indicate that the proposed approach performs considerably better than classical genetic algorithms and dynamic programming.


Genetic Algorithm Dynamic Programming Price Scenario Basic Genetic Algorithm Dynamic Programming Solution 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Sophie Jacquin
    • 1
    • 2
    Email author
  • Laetitia Jourdan
    • 1
    • 2
  • El-Ghazali Talbi
    • 1
    • 2
  1. 1.Inria Lille - Nord EuropeDOLPHIN Project-teamVilleneuve dAscqFrance
  2. 2.Université Lille 1, LIFL, UMR CNRS 8022Villeneuve dAscq cedexFrance

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