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 |
本文献已被 SpringerLink 等数据库收录! |
|