Evaluation of a simulated annealing metaheuristic to solve a forest planning problem

2013 ◽  
Vol 5 (4) ◽  
pp. 376
Author(s):  
Antonio Almeida De Barros Junior ◽  
Gustavo Willam Pereira ◽  
Geraldo Regis Mauri ◽  
Robson De Souza Melo
Keyword(s):  
Simulated Annealing ◽  
Forest Planning ◽  
Planning Problem

scholarly journals Performance of four meta-heuristics to solve a forestry production planning problem

2020 ◽  
Vol 12 ◽  
pp. 1-5
Author(s):  
Emanuelly Canabrava Magalhães ◽  
Carlos Alberto Araújo Júnior ◽  
Francisco Conesa Roca ◽  
Mylla Vyctória Coutinho Sousa
Keyword(s):  
Genetic Algorithm ◽  
Simulated Annealing ◽  
Net Present Value ◽  
Clonal Selection ◽  
Computational Effort ◽  
Neighborhood Search ◽  
Forest Planning ◽  
Planning Problem ◽  
Clonal Selection Algorithm ◽  
Forest Production

The use of artificial intelligence as a tool to aid in the planning of forest production has gained more and more space. Highlighting the metaheuristics, due to the ability to generate optimal solutions for a given optimization problem in a short time, without great computational effort. The present study aims to evaluate the performance of the metaheuristics Genetic Algorithm, Simulated Annealing, Variable Neighborhood Search and Clonal Selection Algorithm applied in a model of regulation of forest production. It was considered a planning horizon of 16 years, in which the model aims to maximize the Net Present Value (NPV), having as restrictions age of cut between 5 and 7 years and minimum and maximum logging demand of 140,000 and 160,000 m3, respectively. Different combinations of configurations were considered for each of the metaheuristics, 30-second processing time and 30 replicates for each configuration, all processing being performed in MeP - Metaheuristics for forest Planning software. The Simulated Annealing metaheuristic obtained the best results when compared to the others, reaching the minimum and maximum demand demanded in all tested configurations, in contrast, the Genetic Algorithm was the one with the worst performance. Thus, the capacity to use metaheuristics as a tool for forest planning is observed.

scholarly journals TUNING OF THE METAHEURISTIC VARIABLE NEIGHBORHOOD SEARCH FOR A FOREST PLANNING PROBLEM

CERNE ◽  
2018 ◽  
Vol 24 (3) ◽  
pp. 259-268
Author(s):  
Carlos Alberto Araújo Júnior ◽  
João Batista Mendes ◽  
Adriana Leandra de Assis ◽  
Christian Dias Cabacinha ◽  
Jonathan James Stocks ◽  
...  
Keyword(s):  
Variable Neighborhood Search ◽  
Neighborhood Search ◽  
Forest Planning ◽  
Planning Problem

Operational Planning Using Mixed Integer Programming

1988 ◽  
Vol 64 (6) ◽  
pp. 485-488 ◽  
Author(s):  
H. Douglas Walker ◽  
Stephen W. Preiss
Keyword(s):  
Planning Process ◽  
Cost Savings ◽  
Mathematical Structure ◽  
Timber Harvesting ◽  
Operational Planning ◽  
Mixed Integer ◽  
Forest Planning ◽  
Planning Problem ◽  
Process Data ◽  
Planning Problems

A mathematical model was constructed and used to help plan five-year timber harvesting and delivery activities from an industrially managed public forest in Ontario. Harvest systems, harvest levels, and wood flows from compartments within the forest to various mills and delivery points were scheduled to minimize costs. The mathematical structure of the model may suggest applications to related forest planning problems. The model was useful in addressing the planning problem, and model results were used within the company's planning process. Data accuracy problems precluded assessing definitively the expected cost savings resulting from model use.

scholarly journals Search reversion within s-metaheuristics: impacts illustrated with a forest planning problem

Silva Fennica ◽  
2015 ◽  
Vol 49 (2) ◽  
Author(s):  
Pete Bettinger ◽  
Mehmet Demirci ◽  
Kevin Boston
Keyword(s):  
Forest Planning ◽  
Planning Problem

scholarly journals Partitioning and solving large-scale tactical harvest scheduling problems for industrial plantation forests

2020 ◽  
Vol 50 (8) ◽  
pp. 811-818
Author(s):  
Pedro Bellavenutte ◽  
Woodam Chung ◽  
Luis Diaz-Balteiro
Keyword(s):  
Large Scale ◽  
Optimization Procedure ◽  
Mixed Integer ◽  
Forest Planning ◽  
Planning Problem ◽  
Optimization Approach ◽  
Scheduling Problems ◽  
Harvest Scheduling ◽  
Plantation Forests ◽  
Industrial Plantation

Spatially explicit, tactical forest planning is a necessary but challenging task in the management of plantation forests. It involves harvest scheduling and planning for road access and log transportation over time and space. This combinatorial problem can be formulated into the fixed-charge transportation problem (FCTP), in which the sum of fixed and variable costs is minimized while meeting harvest volume requirements and allowing necessary road maintenance and log hauling activities. The problem can be solved using general optimization methods such as mixed-integer linear programming (MILP), but the computational efficiency of the MILP-based approach quickly drops as the size and complexity of the problem increases. We developed a new optimization procedure that partitions the large planning problem into smaller subproblems. We applied a hybrid optimization approach using both MILP and heuristic rules to efficiently solve the large FCTP that otherwise may not be solvable using traditional methods. We applied our approach to an industrial plantation forest in Brazil. Our applications demonstrate the performance of the new optimization procedure and the benefit of solving large forest planning problems that integrate harvest scheduling with road access and transportation.

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