University of Jyväskylä | JYX Digital Repository

  • English  | Give feedback |
    • suomi
    • English
 
  • Login
JavaScript is disabled for your browser. Some features of this site may not work without it.
View Item 
  • JYX
  • Artikkelit
  • Informaatioteknologian tiedekunta
  • View Item
JYX > Artikkelit > Informaatioteknologian tiedekunta > View Item

Data-Based Forest Management with Uncertainties and Multiple Objectives

ThumbnailFinal Draft
View/Open
234.4Kb

Downloads:  
Show download detailsHide download details  
Hartikainen, M., Eyvindson, K., Miettinen, K., & Kangas, A. (2016). Data-Based Forest Management with Uncertainties and Multiple Objectives. In P. M. Pardalos, P. Conca, G. Giuffrida, & G. Nicosia (Eds.), Machine Learning, Optimization, and Big Data : Second International Workshop, MOD 2016, Volterra, Italy, August 26-29, 2016, Revised Selected Papers (pp. 16-29). Springer. Lecture Notes in Computer Science, 10122. https://doi.org/10.1007/978-3-319-51469-7_2
Published in
Lecture Notes in Computer Science
Authors
Hartikainen, Markus |
Eyvindson, Kyle |
Miettinen, Kaisa |
Kangas, Annika
Editors
Pardalos, Panos M. |
Conca, Piero |
Giuffrida, Giovanni |
Nicosia, Giuseppe
Date
2016
Copyright
© 2016 Springer International Publishing AG. This is a final draft version of an article whose final and definitive form has been published by Springer. Published in this repository with the kind permission of the publisher.

 
In this paper, we present an approach of employing multiobjective optimization to support decision making in forest management planning. The planning is based on data representing so-called stands, each consisting of homogeneous parts of the forest, and simulations of how the trees grow in the stands under different treatment options. Forest planning concerns future decisions to be made that include uncertainty. We employ as objective functions both the expected values of incomes and biodiversity as well as the value at risk for both of these objectives. In addition, we minimize the risk level for both the income value and the biodiversity value. There is a tradeoff between the expected value and the value at risk, as well as between the value at risk of the two objectives of interest and, thus, decision support is needed to find the best balance between the conflicting objectives. We employ an interactive method where a decision maker iteratively provides preference information to find the most preferred management plan and at the same time learns about the interdependencies of the objectives. ...
Publisher
Springer
Parent publication ISBN
978-3-319-51468-0
Conference
International workshop on machine learning, optimization and big data
Is part of publication
Machine Learning, Optimization, and Big Data : Second International Workshop, MOD 2016, Volterra, Italy, August 26-29, 2016, Revised Selected Papers
ISSN Search the Publication Forum
0302-9743
Keywords
multiobjective optimization interactive multiobjective optimization Pareto optimality metsäsuunnittelu epävarmuus
DOI
https://doi.org/10.1007/978-3-319-51469-7_2
URI

http://urn.fi/URN:NBN:fi:jyu-201701161158

Publication in research information system

https://converis.jyu.fi/converis/portal/detail/Publication/26483352

Metadata
Show full item record
Collections
  • Informaatioteknologian tiedekunta [1592]

Related items

Showing items with similar title or keywords.

  • Integrating risk management tools for regional forest planning : an interactive multiobjective value at risk approach 

    Eyvindson, Kyle; Hartikainen, Markus; Miettinen, Kaisa; Kangas, Annika (NRC Research Press, 2018)
    In this paper, we present an approach employing multiobjective optimization to support decision making in forest management planning under risk. The primary objectives are biodiversity and timber cash flow, evaluated from ...
  • Why Use Interactive Multi-Objective Optimization in Chemical Process Design? 

    Miettinen, Kaisa; Hakanen, Jussi (World Scientific, 2017)
    Problems in chemical engineering, like most real-world optimization problems, typically, have several conflicting performance criteria or objectives and they often are computationally demanding, which sets special requirements ...
  • Why Use Interactive Multi-Objective Optimization in Chemical Process Design? 

    Miettinen, Kaisa; Hakanen, Jussi (World Scientific, 2009)
    Problems in chemical engineering, like most real-world optimization problems, typically, have several conflicting performance criteria or objectives and they often are computationally demanding, which sets special requirements ...
  • Multi-scenario multi-objective robust optimization under deep uncertainty : A posteriori approach 

    Shavazipour, Babooshka; Kwakkel, Jan H.; Miettinen, Kaisa (Elsevier BV, 2021)
    This paper proposes a novel optimization approach for multi-scenario multi-objective robust decision making, as well as an alternative way for scenario discovery and identifying vulnerable scenarios even before any solution ...
  • Interactive multiobjective optimization with NIMBUS for decision making under uncertainty 

    Miettinen, Kaisa; Mustajoki, Jyri; Stewart, Theodor J. (Springer, 2014)
    We propose an interactive method for decision making under uncertainty, where uncertainty is related to the lack of understanding about consequences of actions. Such situations are typical, for example, in design problems, ...
  • Browse materials
  • Browse materials
  • Articles
  • Conferences and seminars
  • Electronic books
  • Historical maps
  • Journals
  • Tunes and musical notes
  • Photographs
  • Presentations and posters
  • Publication series
  • Research reports
  • Research data
  • Study materials
  • Theses

Browse

All of JYXCollection listBy Issue DateAuthorsSubjectsPublished inDepartmentDiscipline

My Account

Login

Statistics

View Usage Statistics
  • How to publish in JYX?
  • Self-archiving
  • Publish Your Thesis Online
  • Publishing Your Dissertation
  • Publication services

Open Science at the JYU
 
Data Protection Description

Accessibility Statement

Unless otherwise specified, publicly available JYX metadata (excluding abstracts) may be freely reused under the CC0 waiver.
Open Science Centre