A Progressive Hedging Approach to Solve Harvest Scheduling Problem under Climate Change
by
Jordi Garcia-Gonzalo 1,2,*
, Cristóbal Pais 3,4, Joanna Bachmatiuk 2, Susana Barreiro 2 and Andres Weintraub 3,*
Jordi Garcia-Gonzalo 1,2,*, Cristóbal Pais 3,4, Joanna Bachmatiuk 2, Susana Barreiro 2 and Andres Weintraub 3,*
1
Forest Science and Technology Centre of Catalonia, Solsona, 08930 Catalonia, Spain
2
Centro de Estudos Florestais, Instituto Superior de Agronomia, Universidade de Lisboa, 1500-020 Lisboa, Portugal
3
Ingenieria Industrial, Universidad de Chile, Santiago 7591538, Chile
4
4IEOR Department at UC Berkeley, California, CA 95101, USA
*
Authors to whom correspondence should be addressed.
Forests 2020, 11(2), 224; https://doi.org/10.3390/f11020224
Received: 18 October 2019 / Revised: 12 February 2020 / Accepted: 13 February 2020 / Published: 17 February 2020
(This article belongs to the Special Issue Adaptive Forest Management and Decision Making Models under Climate Change (Risk and Uncertainty))
Due to the long time horizon typically characterizing forest planning, uncertainty plays an important role when developing forest management plans. Especially important is the uncertainty related to recently human-induced global warming since it has a clear impact on forest capacity to contribute to biogenic and anthropogenic ecosystem services. If the forest manager ignores uncertainty, the resulting forest management plan may be sub-optimal, in the best case. This paper presents a methodology to incorporate uncertainty due to climate change into forest management planning. Specifically, this paper addresses the problem of harvest planning, i.e., defining which stands are to be cut in each planning period in order to maximize expected net revenues, considering several climate change scenarios. This study develops a solution approach for a planning problem for a eucalyptus forest with 1000 stands located in central Portugal where expected future conditions are anticipated by considering a set of climate scenarios. The model including all the constraints that link all the scenarios and spatial adjacency constraints leads to a very large problem that can only be solved by decomposing it into scenarios. For this purpose, we solve the problem using Progressive Hedging (PH) algorithm, which decomposes the problem into scenario sub-problems easier to solve. To analyze the performance of PH versus the use of the extensive form (EF), we solve several instances of the original problem using both approaches. Results show that PH outperforms the EF in both solving time and final optimality gap. In addition, the use of PH allows to solve the most difficult problems while the commercial solvers are not able to solve the EF. The approach presented allows the planner to develop more robust management plans that incorporate the uncertainty due to climate change in their plans.
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MDPI and ACS Style
Garcia-Gonzalo, J.; Pais, C.; Bachmatiuk, J.; Barreiro, S.; Weintraub, A. A Progressive Hedging Approach to Solve Harvest Scheduling Problem under Climate Change. Forests 2020, 11, 224.
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