Optimal parameter settings for solving harvest scheduling models with adjacency constraints

Phillip J. Manning, Marc E. McDill

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

Optimal parameter settings to improve the efficiency of solving harvest scheduling models with adjacency constraints were examined using Ilog's Cplex ® 11.2 optimizer tuning tool. A total of 160 randomly generated hypothetical forests were created with either 50 or 100 stands and four age-class distributions. Mixed integer programming problems were formulated in Model I form with four different adjacency constraint types, two Unit Restriction Model (URM) adjacency constraints (Pairwise and Maximal Clique) and two Area Restriction Model (ARM) formulations (Path and Generalized Management Unit). A total of 640 problem sets-where a set is a common forest size, age-class distribution, and adjacency constraint type-were tuned to determine optimal parameter settings and then were solved at both the default and optimal settings. In general, mean solution time was less for a given problem set using the optimal parameters compared to the default parameters. The results discussed provide a simple approach to decrease the solution time of solving mixed integer forest planning problems with adjacency constraints.

Original languageEnglish (US)
Pages (from-to)16-26
Number of pages11
JournalMathematical and Computational Forestry and Natural-Resource Sciences
Volume4
Issue number1
StatePublished - Feb 28 2012

All Science Journal Classification (ASJC) codes

  • Forestry
  • Environmental Engineering
  • Computer Science Applications
  • Applied Mathematics

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