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Articles by Jordi Garcia-Gonzalo
Category : Research article
article id 1326,
category
Research article
Joanna Bachmatiuk,
Jordi Garcia-Gonzalo,
Jose Guilherme Borges.
(2015).
Analysis of the performance of different implementations of a heuristic method to optimize forest harvest scheduling.
Silva Fennica
vol.
49
no.
4
article id 1326.
https://doi.org/10.14214/sf.1326
Highlights:
The number of treatment schedules available for each stand has an impact on the optimal configuration of opt-moves (i.e. number stands where the treatment schedule is changed in an iteration); Considering a large number of treatment schedules per stand, the one-opt move implementation is preferred, yet when considering a low number of decision choices the two-opt moves option performs better.
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Finding an optimal solution of forest management scheduling problems with even flow constraints while addressing spatial concerns is not an easy task. Solving these combinatorial problems exactly with mixed-integer programming (MIP) methods may be infeasible or else involve excessive computational costs. This has prompted the use of heuristics. In this paper we analyze the performance of different implementations of the Simulated Annealing (SA) heuristic algorithm for solving three typical harvest scheduling problems. Typically SA consists of searching a better solution by changing one decision choice in each iteration. In forest planning this means that one treatment schedule in a single stand is changed in each iteration (i.e. one-opt move). We present a comparison of the performance of the typical implementation of SA with the new implementation where up to three decision choices are changed simultaneously in each iteration (i.e. treatment schedules are changed in more than one stand). This may allow avoiding local optimal. In addition, the impact of SA - parameters (i.e. cooling schedule and initial temperature) are tested. We compare our heuristic results with a MIP formulation. The study case is tested in a real forest with 1000 stands and a total of 213116 decision choices. The study shows that when the combinatorial problem is very large, changing simultaneously the treatment schedule in more than one stand does not improve the performance of SA. Contrarily, if we reduce the size of the problem (i.e. reduce considerably the number of alternatives per stand) the two-opt moves approach performs better.
-
Bachmatiuk,
Centro de Estudos Florestais, Instituto Superior de Agronomia, Universidade de Lisboa, Lisboa, Portugal
E-mail:
jbachmatiuk@isa.ulisboa.pt
- Garcia-Gonzalo, Centro de Estudos Florestais, Instituto Superior de Agronomia, Universidade de Lisboa, Lisboa, Portugal E-mail: jordigarcia@isa.ulisboa.pt
- Borges, Centro de Estudos Florestais, Instituto Superior de Agronomia, Universidade de Lisboa, Lisboa, Portugal E-mail: joseborges@isa.ulisboa.pt
article id 441,
category
Research article
Ane Zubizarreta-Gerendiain,
Petri Pellikka,
Jordi Garcia-Gonzalo,
Veli-Pekka Ikonen,
Heli Peltola.
(2012).
Factors affecting wind and snow damage of individual trees in a small management unit in Finland: assessment based on inventoried damage and mechanistic modelling.
Silva Fennica
vol.
46
no.
2
article id 441.
https://doi.org/10.14214/sf.441
Keywords:
Pinus sylvestris;
Picea abies;
Betula spp.;
critical wind speed;
snow loading;
damage risk
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In this work, we assessed the factors affecting wind and snow damage of individual trees in a small management unit in western Finland. This was done based on inventoried damage and observed wind speeds and snow loading in storms Pyry and Janika in 2001 and Mielikki in 2002 together with mechanistic model. First, we studied which factors explain the observed damage in individual trees. Secondly, we studied how well the mechanistic model (HWIND) could predict the wind speed needed to uproot individual trees at the margins of permanent upwind edges. We found that Pyry storm caused 70% and Janika and Mielikki 18 and 12% of observed damage. In Janika storm, all trees uprooted. In other storms, both uprooting and stem breakage occurred. Scots pine suffered the most damage. Recently thinned stands on the upwind edges of open areas suffered the most damage. But, damage occurred also on soils with relatively shallow anchorage. HWIND predicted correctly damage for 69% of all uprooted trees. No-uprooting was correctly predicted for 45 and 19% of standing trees (all Scots pines), which were measured within and at the immediate upwind edge of same stands. HWIND model needs further validation at the permanent edges and/or on soils with shallow rooting to improve its prediction accuracy in such conditions.
- Zubizarreta-Gerendiain, Technical University of Lisbon, School of Agriculture, Forest Research Centre, Lisbon, Portugal E-mail: azg@nn.po
- Pellikka, University of Helsinki, Dept. of Geosciences and Geography, Helsinki, Finland E-mail: pp@nn.fi
- Garcia-Gonzalo, Technical University of Lisbon, School of Agriculture, Forest Research Centre, Lisbon, Portugal E-mail: jgg@nn.po
- Ikonen, University of Eastern Finland, School of Forest Sciences, Joensuu, Finland E-mail: vpi@nn.fi
-
Peltola,
University of Eastern Finland, School of Forest Sciences, Joensuu, Finland
E-mail:
heli.peltola@uef.fi
article id 32,
category
Research article
Susete Marques,
Jordi Garcia-Gonzalo,
José G. Borges,
Brigite Botequim,
M. Manuela Oliveira,
José Tomé,
Margarida Tomé.
(2011).
Developing post-fire Eucalyptus globulus stand damage and tree mortality models for enhanced forest planning in Portugal.
Silva Fennica
vol.
45
no.
1
article id 32.
https://doi.org/10.14214/sf.32
Keywords:
forest fires;
forest management;
Eucalyptus globulus Labill;
damage model;
post-fire mortality
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Forest and fire management planning activities are carried out mostly independently of each other. This paper discusses research aiming at the development of methods and tools that can be used for enhanced integration of forest and fire management planning activities. Specifically, fire damage models were developed for Eucalyptus globulus Labill stands in Portugal. Models are based on easily measurable forest characteristics so that forest managers may predict post-fire mortality based on forest structure. For this purpose, biometric data and fire-damage descriptors from 2005/2006 National Forest Inventory plots and other sample plots within 2006, 2007 and 2008 fire areas were used. A three-step modelling strategy based on logistic regression methods was used. In the first step, a model was developed to predict whether mortality occurs after a wildfire in a eucalypt stand. In the second step the degree of damage caused by wildfires in stands where mortality occurs is quantified (i.e. percentage of mortality). In the third step this mortality is distributed among trees. Data from over 85 plots and 1648 trees were used for modeling purposes. The damage models show that relative damage increases with stand basal area. Tree level mortality models indicate that trees with high diameters, in dominant positions and located in regular stands are less prone to die when a wildfire occurs.
-
Marques,
Technical University of Lisbon, School of Agriculture, Forest Research Center, Tapada da Ajuda, 1349-017 Lisboa, Portugal
E-mail:
smarques@isa.utl.pt
- Garcia-Gonzalo, Technical University of Lisbon, School of Agriculture, Forest Research Center, Tapada da Ajuda, 1349-017 Lisboa, Portugal E-mail: jgg@nn.pt
- Borges, Technical University of Lisbon, School of Agriculture, Forest Research Center, Tapada da Ajuda, 1349-017 Lisboa, Portugal E-mail: jgb@nn.pt
- Botequim, Technical University of Lisbon, School of Agriculture, Forest Research Center, Tapada da Ajuda, 1349-017 Lisboa, Portugal E-mail: bb@nn.pt
- Oliveira, Technical University of Lisbon, School of Agriculture, Forest Research Center, Tapada da Ajuda, 1349-017 Lisboa, Portugal E-mail: mmo@nn.pt
- Tomé, Technical University of Lisbon, School of Agriculture, Forest Research Center, Tapada da Ajuda, 1349-017 Lisboa, Portugal E-mail: jt@nn.pt
- Tomé, Technical University of Lisbon, School of Agriculture, Forest Research Center, Tapada da Ajuda, 1349-017 Lisboa, Portugal E-mail: mt@nn.pt
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