@article{Lu:197904,
      recid = {197904},
      author = {Lu, Fadian},
      title = {A Hybrid Heuristic Algorithm for Harvest Decision of Mixed  Species Stand under Price Risk},
      journal = {Scandinavian Forest Economics: Proceedings of the Biennial  Meeting of the Scandinavian Society of Forest Economics},
      address = {2004-05},
      number = {1329-2016-103675},
      pages = {11},
      year = {2004},
      abstract = {In this article, a hybrid heuristic algorithm based in  Genetic Algorithm and Hooke and Jeeves in described for  solving a complicated forest harvest decision problem,  which involves optimization of thinning and final felling  under price risk for a mixed species stand of spruce and  pine.  The strategy consists of two optimal stocking level  functions and one reservation price function; in which,  there are ten variables need to be optimized. The hybrid  heuristic algorithm consists of two stages. At the first  stage the Hooke and Jeeves is applied to find the optimal  solutions using these initial solutions. As the benchmark,  a pure Genetic Algorithm, Hook and Jeeves, and Powell  search are also tested. Results show that the hybrid  heuristic algorithm is the best one among all of the tested  algorithm. Genetic Algorithm ranks second, Hooke and Jeeves  the third and Powell search is the worst.},
      url = {http://ageconsearch.umn.edu/record/197904},
      doi = {https://doi.org/10.22004/ag.econ.197904},
}