Harvest Scheduling Subject to Maximum Area Restrictions: Exploring Exact Approaches

Authors:
Marcos Goycoolea;Alan T. Murray;Francisco Barahona;Rafael Epstein;Andrés Weintraub
Affiliations:
-;-;-;-;-
Venue:
Operations Research
Year:
2005

Citing 0
Cited 6

Review of combinatorial problems induced by spatial forest harvesting planning

Discrete Applied Mathematics - Special issue: IV ALIO/EURO workshop on applied combinatorial optimization
Operations Research Models and the Management of Agricultural and Forestry Resources: A Review and Comparison

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Lagrangean relaxation with clusters for point-feature cartographic label placement problems

Computers and Operations Research
Review of combinatorial problems induced by spatial forest harvesting planning

Discrete Applied Mathematics - Special issue: IV ALIO/EURO workshop on applied combinatorial optimization
Quantitative Methods for a New Configuration of Territorial Units in a Chilean Government Agency Tender Process

Interfaces
A branch-and-price approach for harvest scheduling subject to maximum area restrictions

Computational Optimization and Applications

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Abstract

We consider a spatial problem arising in forest harvesting. For regulatory reasons, blocks harvested should not exceed a certain total area, typically 49 hectares. Traditionally, this problem, called the adjacency problem, has been approached by forming a priori blocks from basic cells of 5 to 25 hectares and solving the resulting mixed-integer program. Superior solutions can be obtained by including the construction of blocks in the decision process. The resulting problem is far more complex combinatorially. We present an exact algorithmic approach that has yielded good results in computational tests. This solution approach is based on determining a strong formulation of the linear programming problem through a clique representation of a projected problem.