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Permanent link (DOI): https://doi.org/10.7939/R3239X

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Theses and Dissertations

Development of a Genetic Algorithm Model for a Multiple-Objective Forest Harvesting and Zonation Problem Open Access

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Other title
Subject/Keyword
Genetic Algorithm
Multiple-Objective
Mixed integer programming model
Forest Zonation
Type of item
Thesis
Degree grantor
University of Alberta
Author or creator
Kuloglu, Tevfik Z
Supervisor and department
Armstrong, Glen (Renewable Resources)
Examining committee member and department
Luckert, Martin (Resources of Economics and Environmental Sociology)
Jeffrey, Scott (Resources of Economics and Environmental Sociology)
Department
Department of Renewable Resources
Specialization
Forest Biology and Management
Date accepted
2014-07-04T13:31:07Z
Graduation date
2014-11
Degree
Master of Science
Degree level
Master's
Abstract
Most of the forested lands in North America are managed for multiple objectives and forest management plans are designed in a manner to obtain or maintain sustainable forest management certification. One strategy for achieving some of these goals is forest zonation, which allows for different intensities of forest management (including reserve areas) in different zones of the forest. The focus of this thesis is the development of a spatially explicit forest estate model which simultaneously allocates forest land to different management intensity zones and harvest periods with the goal of satisfying multiple management objectives. The model was initially developed using mixed integer goal programming. This helped to identify a basic model structure which was used to guide the development of a genetic algorithm-based implementation. The development of the model, particularly the setting of goal weights to describe the decision maker's preferences is described in detail.
Language
English
DOI
doi:10.7939/R3239X
Rights
Permission is hereby granted to the University of Alberta Libraries to reproduce single copies of this thesis and to lend or sell such copies for private, scholarly or scientific research purposes only. Where the thesis is converted to, or otherwise made available in digital form, the University of Alberta will advise potential users of the thesis of these terms. The author reserves all other publication and other rights in association with the copyright in the thesis and, except as herein before provided, neither the thesis nor any substantial portion thereof may be printed or otherwise reproduced in any material form whatsoever without the author's prior written permission.
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