scholarly journals Analysis of the performance of different implementations of a heuristic method to optimize forest harvest scheduling

Silva Fennica ◽  
2015 ◽  
Vol 49 (4) ◽  
Author(s):  
Joanna Bachmatiuk ◽  
Jordi Garcia-Gonzalo ◽  
Jose Borges
Keyword(s):  
Heuristic Method ◽  
Harvest Scheduling ◽  
Forest Harvest

scholarly journals EFEITO DAS RESTRIÇÕES ESPACIAIS DE ADJACÊNCIA NO PLANEJAMENTO FLORESTAL OTIMIZADO

FLORESTA ◽  
2010 ◽  
Vol 40 (3) ◽  
Author(s):  
Lucas Rezende Gomide ◽  
Julio Eduardo Arce ◽  
Arinei Lindbeck da Silva
Keyword(s):  
Linear Programming ◽  
Integer Linear Programming ◽  
Net Present Value ◽  
Forest Planning ◽  
Type I ◽  
Harvest Scheduling ◽  
Forest Harvest ◽  
Horizon Planning ◽  
Management Alternatives ◽  
The Impact

O objetivo do estudo foi aplicar restrições espaciais de adjacência no agendamento da colheita florestal em um modelo tradicional de planejamento florestal. Foi analisado e comparado o impacto no VPL (valor presente líquido) e na produção volumétrica de madeira. A área de estudo foi composta por 52 talhões de eucalipto. Foram simuladas 254 alternativas de manejo, sendo então criados 4 cenários de agendamento da colheita florestal envolvendo o uso da programação linear inteira, seguindo a formulação pelo modelo tipo I com maximização do VPL e um horizonte de planejamento de 7 anos. O cenário 1 não considerou a adjacência, enquanto que os cenários 2 (URM), 3 (ARM50) e 4 (ARM70) continham restrições de adjacência. Os resultados demonstraram que as restrições de adjacência reduzem o VPL em 3,74%, 2,24% e 2,10%, e a produção volumétrica em 2,92%, 1,79% e 1,73%, nos cenários 2, 3 e 4 respectivamente. Porém, os cenários 2, 3 e 4 obtiveram sucesso no controle de corte de talhões adjacentes, segundo suas restrições, e impedindo a formação de extensas áreas contiguas como encontrado no cenário 1 (153,25 ha).Palavras-chave: Programação linear inteira; restrição URM; restrição ARM. AbstractSpatial adjacency constraints effect in optimized forest planning. The objective of the study was to apply the spatial adjacency constraints in the forest harvest scheduling when using the traditional forest planning model. It was analyzed and compared the impact on NPV (Net Present Value) and the volumetric production of wood. The area of study was formed by 52 stands of eucalyptus. A total of 254 forest management alternatives were simulated, where 4 forest harvest scheduling scenarios contained the integer linear programming were created, following the model type I and the maximization of the NPV for 7 years of the horizon planning. Spatial adjacency constraints were applied to scenarios 2 (URM), 3 (ARM50) and 4 (ARM70) but not to scenario 1. The results showed that the spatial adjacency constraints reduced NPV in 3,74%, 2,24% and 2,10%, and the volumetric production in 2,92%, 1,79% e 1,73% through the scenarios 2, 3, and 4, respectively. Therefore, the scenarios 2, 3, and 4 obtained success in controlling the adjacent harvested stands, according to their restrictions, and avoiding the creation of large and continuous areas such as observed in the scenario 1 (153,25ha).Keywords: Integer linear programming; URM constraint; ARM constraint.

A simple way to incorporate uncertainty and risk into forest harvest scheduling

2016 ◽  
Vol 359 ◽  
pp. 11-18 ◽  
Author(s):  
Andrew P. Robinson ◽  
Michael McLarin ◽  
Ian Moss
Keyword(s):  
Harvest Scheduling ◽  
Forest Harvest

Goal programming for reconciling economic, even-flow, and regulation objectives in forest harvest scheduling

1979 ◽  
Vol 9 (4) ◽  
pp. 525-531 ◽  
Author(s):  
Chiang Kao ◽  
J. Douglas Brodie
Keyword(s):  
Goal Programming ◽  
Compromise Solution ◽  
Optimal Solutions ◽  
Harvest Scheduling ◽  
Forest Harvest ◽  
Net Worth

To resolve the traditional quantifiable but incommensurate objectives of perfect regulation, maximization of present net worth, and even-flow harvest, goal programming (GP) was applied to a sample forest, providing optimal solutions for each goal and a compromise solution that jointly considered all three as weighted goals. Goal programming overcame problems of infeasible specification and satisfied alternate criteria in cases with multiple optima. The GP approach provided a means of considering each of the three goals and minimizing the appropriately weighted deviations.

Optimal harvest scheduling at the forest level in the presence of the risk of fire

1986 ◽  
Vol 16 (2) ◽  
pp. 266-278 ◽  
Author(s):  
W. J. Reed ◽  
D. Errico
Keyword(s):  
Dynamic Equations ◽  
Scheduling Problem ◽  
Deterministic Approach ◽  
Harvest Scheduling ◽  
Forest Harvest ◽  
Timber Supply ◽  
Reasonable Approximation ◽  
Optimal Harvest ◽  
The Impact ◽  
Scheduling Models

The effect of fire on forest yields has been well documented in stand-level analyses; however, forest-level effects are less widely known. A set of dynamic equations can be constructed that describe the evolution of a forest under the impact of harvesting and random fire. When fire is treated in a deterministic fashion, these equations can be used to formulate an optimal harvest scheduling problem that can be solved using linear programming. Examples using white spruce data for the Fort Nelson Timber Supply Area of British Columbia show that even modest rates of fire can have a dramatic impact and that present harvest scheduling models may be considerably overestimating projected forest harvest levels. Results also show that the deterministic approach appears to be a reasonable approximation of the true stochastic fire problem.

Formulating the integrated forest harvest-scheduling model to reduce the cost of the road-networks

2018 ◽  
Vol 20 (4) ◽  
pp. 2283-2306 ◽  
Author(s):  
Nader Naderializadeh ◽  
Kevin A. Crowe
Keyword(s):  
Road Networks ◽  
Harvest Scheduling ◽  
Forest Harvest ◽  
The Road ◽  
Scheduling Model ◽  
The Cost

A multi-objective Monte Carlo tree search for forest harvest scheduling

2020 ◽  
Vol 282 (3) ◽  
pp. 1115-1126 ◽  
Author(s):  
Teresa Neto ◽  
Miguel Constantino ◽  
Isabel Martins ◽  
João Pedro Pedroso
Keyword(s):  
Monte Carlo ◽  
Tree Search ◽  
Harvest Scheduling ◽  
Forest Harvest ◽  
Monte Carlo Tree Search ◽  
Multi Objective

scholarly journals Application of Linear Goal Programming to Forest Harvest Scheduling

1983 ◽  
Vol 15 (1) ◽  
pp. 103-108 ◽  
Author(s):  
James E. Hotvedt
Keyword(s):  
Forest Management ◽  
Goal Programming ◽  
Harvest Scheduling ◽  
Forest Harvest ◽  
Long Period ◽  
Linear Goal Programming

Forest management and planning is complex, involving the application of many scarce and diverse resources to the production and maintenance of a multitude of products and services from the forest over a relatively long period of time.

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