Please use this identifier to cite or link to this item: https://knowledgecommons.lakeheadu.ca/handle/2453/913
Title: Integrated resource management planning through the linking of mathematical and judgement-based models
Authors: Tak, Kwang-Il
Keywords: Natural resources Management Mathematical models;Natural resources Management;Forest management Mathematical models;Forest resource policy;Sibley Provincial Park
Issue Date: 1988
Abstract: The objective of this study was to develop an analytical technique to enable forest managers to handle effectively the complex problem of integrated resource management planning using quantitative and qualitative information. Two different types of modelling approaches were used: 1) a quantitative-oriented linear goal programming and 2) a qualitative-oriented IDA model. These two types of model were linked to complement each other. By means of an inter-disciplinary workshop approach, an attempt was made to strengthen and broaden the power of the models to represent real world problems. Timber, wildlife and outdoor recreation-related objectives and variables were used for this study. Sibley Provincial Park in Ontario, Canada, was used for the trial application of this approach. A ten-year planning horizon and four cutting alternatives were employed. A resource policy which provided all interest groups in the workshop with the highest satisfaction levels was developed. The forest land in the study area was allocated optimally to achieve the multiple objectives of timber, wildlife and outdoor recreation. Determining target levels and weights for goal programming application were improved by linking LP and IDA processes. Subjective judgements of workshop participants were partly assisted and improved by initial LP solutions.
URI: http://knowledgecommons.lakeheadu.ca/handle/2453/913
metadata.etd.degree.discipline: Forestry and the Forest Environment
metadata.etd.degree.name: Master of Science
metadata.etd.degree.level: Master
metadata.dc.contributor.advisor: Benson, C. A.
Appears in Collections:Retrospective theses

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