A Novel Two-Phase Approach to Forest Harvesting Optimization Using Cable Logging

被引:1
作者
Rey, Carlos [1 ,2 ]
Sandoval, Simon [3 ]
Cabrera-Vives, Guillermo [1 ,4 ]
Seco, Diego [5 ]
Cerulo, Pierluigi [4 ]
Li, Zheng [6 ]
机构
[1] Univ Concepcion, Data Sci Unit, Concepcion 4070409, Chile
[2] Univ Bio Bio, Dept Ingn Ind, Concepcion 3780000, Chile
[3] Univ Concepcion, Fac Ciencias Forestales, Dept Manejo Bosques & Medio Ambiente, Lab Anal & Modelamiento Geoinformac, Concepcion 4070409, Chile
[4] Univ Concepcion, Dept Comp Sci, Concepcion 4070409, Chile
[5] Univ A Coruna, Ctr Invest TIC, La Coruna 15071, Spain
[6] Queens Univ Belfast, Sch EEECS, Belfast BT7 1NN, Antrim, North Ireland
关键词
cable-yarding; discrete location; heuristics; integer programming; genetic algorithm; LOCATION; MODELS;
D O I
10.3390/f14112133
中图分类号
S7 [林业];
学科分类号
0829 ; 0907 ;
摘要
Timber extraction is a vital process in forest harvesting, particularly in areas with high slopes where timber harvesting methods are not feasible. In such cases, logging towers employing extraction cables are often the most effective solution. This intricate task involves several phases, with the installation of the tower being one of the most critical. It significantly influences the performance and feasibility of timber extraction. Another crucial phase involves strategically positioning logging lines to minimize the installation time while maximizing the load capacity efficiency. This article presents an integer programming mathematical model for determining the optimal positioning of yarders conditioned to logging lines, the timber logging time, and the logging cycle time. Furthermore, a two-phase heuristic algorithm is introduced to address the problem. Both approaches offer a preliminary proposal for the location of logging towers and the arrangement of logging lines within a two-dimensional spatial plane, thereby streamlining the timber extraction process in challenging terrains. Finally, we compare manually generated approximate planning (referred to as the manual planning approach, MPA) with our presented approaches. Our methods outperform the MPA, and notably, our two-phase approach surpasses solvers commonly used in the industry by up to 38% in real case studies.
引用
收藏
页数:26
相关论文
共 20 条
[1]   Object Detection through Modified YOLO Neural Network [J].
Ahmad, Tanvir ;
Ma, Yinglong ;
Yahya, Muhammad ;
Ahmad, Belal ;
Nazir, Shah ;
ul Haq, Amin .
SCIENTIFIC PROGRAMMING, 2020, 2020 :1-10
[2]  
BALAS E, 1980, MATH PROGRAM STUD, V12, P37, DOI 10.1007/BFb0120886
[3]  
Bharati Puja, 2020, Computational Intelligence in Pattern Recognition. Proceedings of CIPR 2019. Advances in Intelligent Systems and Computing (AISC 999), P657, DOI 10.1007/978-981-13-9042-5_56
[4]   Optimizing cable harvesting layout when using variable-length cable roads in central Europe [J].
Bont, Leo ;
Heinimann, Hans Rudolf ;
Church, Richard L. .
CANADIAN JOURNAL OF FOREST RESEARCH, 2014, 44 (08) :949-960
[5]   Tensile forces and deflections on skylines of cable yarders: comparison of measurements with close-to-catenary predictions [J].
Bont, Leo Gallus ;
Ramstein, Laura ;
Frutig, Fritz ;
Schweier, Janine .
INTERNATIONAL JOURNAL OF FOREST ENGINEERING, 2022, 33 (03) :195-216
[6]   Location set-covering inspired models for designing harvesting and cable road layouts [J].
Bont, Leo Gallus ;
Church, Richard L. .
EUROPEAN JOURNAL OF FOREST RESEARCH, 2018, 137 (06) :771-792
[7]   Concurrent optimization of harvesting and road network layouts under steep terrain [J].
Bont, Leo Gallus ;
Heinimann, Hans Rudolf ;
Church, Richard L. .
ANNALS OF OPERATIONS RESEARCH, 2015, 232 (01) :41-64
[8]  
Darwin C., 1859, On the Origin of Species: A Facsimile of the First Edition
[9]  
Dykstra D. P., 1977, AIIE Transactions, V9, P270, DOI 10.1080/05695557708975155
[10]  
EIBEN AE, 2003, INTRO EVOLUTIONARY C, P37, DOI DOI 10.1007/978-3-662-05094-1