Performances of Two Prototypes of Log Extraction Techniques Using the Skyline System

Endom, Wesman; Astana, Satria

doi:10.20886/ijfr.2017.4.1.1-14

Cited by 1 publication

(2 citation statements)

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“…This system may operate over a large area and is being widely practiced in several areas such as in Northern California, United State of America (USA) (Hwang et al 2018), Lushoto Tanzania (Dos Santos 2015, Italy (Proto and Zimbalatti 2016), and France (Spinelli et al 2017). In tropical forests, this skyline harvesting system found to be useful and more practical in Indonesia (Endom and Astana 2017). A study conducted in 2011 and 2013 by Endom and Astana (2017) found skyline logging as effective at steep slopes ranging from 40% to 60% in terms of timber volumes.…”

Section: Significance Of Forest Transportation Studiesmentioning

confidence: 99%

“…In tropical forests, this skyline harvesting system found to be useful and more practical in Indonesia (Endom and Astana 2017). A study conducted in 2011 and 2013 by Endom and Astana (2017) found skyline logging as effective at steep slopes ranging from 40% to 60% in terms of timber volumes. In Malaysia, however, there are limitations to use helilogging and skyline harvesting systems in forest harvesting due to higher operational costs and denser tropical stand structures (Pinard et al 1995;Bigsby and Ling 2013).…”

Section: Significance Of Forest Transportation Studiesmentioning

confidence: 99%

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Bees algorithm for Forest transportation planning optimization in Malaysia

Jamaluddin

Norizah

Hasmadi

et al. 2021

Forest Science and Technology

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Algorithm is widely used in various areas due to its ability to solve classes of problems. Due to multiple objectives to be met and varied algorithm application in this digital era, addressing the problem-solving optimization in a more efficient and effective way has become more reasonable. Forest transportation planning is one of the most expensive activities in timber harvesting and can be optimized through algorithm application. Forest transportation planning is a vital component of timber harvesting activities. Inappropriate planning may raise the overall costs of harvesting activities. This paper aims to give an overview of several algorithm application in optimizing the forest transportation planning problem and give an insightful information regarding the relationships between algorithm and the integration of transportation system characteristics and variables. Examples of algorithm that are finding their way to the forest transportation planning problem include Genetic Algorithm (GA), Particle Swarm Optimization (PSO) algorithm, Ant Colony Optimization (ACO) algorithm, Simulated Annealing (SA) algorithm and Tabu Search (TS) algorithm. Although no literature was found regarding forest transportation planning problem optimization with regards to Bees Algorithm (BA), rules set for several transportation problem evidenced from literature search seems to be applicable to forestry. Generally, in this paper, the BA has been given focus for forest transportation planning problem optimization as a potential algorithm to overcome the challenges of environmental degradation and efficiency of timber extraction used, as well as its accuracy and less processing time for problem-solving.

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