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Forest management models and combinatorial algorithms: analysis of state of the art
Authors:Andres Weintraub  Richard L Church  Alan T Murray  Monique Guignard
Institution:(1) Department of Industrial Engineering, University of Chile, P.O. Box 2777, Santiago, Chile Email;(2) National Center for Geographic Information and Analysis and the Department of Geography, University of California at Santa Barbara, Santa Barbara, CA 93106, USA;(3) Department of Geography, Ohio State University, Columbus, OH 43210, USA;(4) Department of Operations and Information Management, The Wharton School, University of Pennsylvania, Philadelphia, PA 19104, USA
Abstract:Linear Programming and Mixed Integer Linear Programs have been used for forest planning since the 60's to support decision making on forest harvesting and management. In particular, during the last two decades of forest management there has been an increased interest in spatial issues. Further, new environmental concerns, such as resource sustainability and wildlife protection, impose that increased attention be paid to activities carried out on the ground. Road building needed for access also requires spatial definiton. As a result, more complex models must be used. We discuss the issues which have led to the combinatorial nature of some main forest management problems and the solution algorithms that have been proposed for these problems, including local search heuristics, random search approaches, strengthening of mixed integer model formulations and Lagrangian relaxation. In this survey, we discuss which of the proposed approaches have been used succesfully, the advantages and shortcomings of each and what are still open research problems. This revised version was published online in June 2006 with corrections to the Cover Date.
Keywords:spatial decisions  mixed integer models  forest management  combinatorial problems  heuristics
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