RT Journal Article
T1 Multi-objective models for the forest harvest scheduling problem in a continuous-time framework
A1 González González, Manuel
A1 Vázquez Méndez, Miguel Ernesto
A1 Diéguez Aranda, Ulises
K1 Even-aged forest management
K1 Land and timber value
K1 Forest regulation
K1 Continuous optimization
K1 Gradient-based optimization
K1 Pareto frontier
AB In this study we present several multi-objective models for forest harvest scheduling in forest with single-species, even-aged stands using a continuous formulation. We seek to maximize economic profitability and even-flow of timber harvest volume, both for the first rotation and for the regulated forest. For that, we design new metrics that allow working with continuous decision variables, namely, the harvest time of each stand. Unlike traditional combinatorial formulations, this avoids dividing the planning horizon into periods and simulating alternative management prescriptions before the optimization process. We propose to combine a scalarization technique (weighting method) with a gradient-type algorithm (L-BFGS-B) to obtain the Pareto frontier of the problem, which graphically shows the relationships (trade-offs) between objectives, and helps the decision makers to choose a suitable weighting for each objective. We compare this approach with the widely used in forestry multi-objective evolutionary algorithm NSGA-II. We analyze the model in a Eucalyptus globulus Labill. forest of Galicia (NW Spain). The continuous formulation proves robust in forests with different structures and provides better results than the traditional combinatorial approach. For problem solving, our proposal shows a clear advantage over the evolutionary algorithm in terms of computational time (efficiency), being of the order of 65 times faster for both continuous and discrete formulations
PB Elsevier
YR 2022
FD 2022
LK http://hdl.handle.net/10347/27596
UL http://hdl.handle.net/10347/27596
LA eng
NO Forest Policy and Economics 136 (2022) 102687
DS Minerva
RD 23 abr 2026