Speaker
Description
Selective logging in structurally complex stands requires technologically flexible skidding systems capable of operating under pronounced environmental and operational uncertainty. Variability in terrain morphology, soil bearing capacity, timber assortment dimensions, and dynamic resistance to motion creates a stochastic decision environment in which conventional deterministic design approaches prove insufficient. In practice, this often results in either excessive energy consumption and underutilised traction potential or increased soil disturbance due to inappropriate parameter settings of technological equipment. Therefore, a scientifically grounded framework for the justification of skidding machine parameters is required, capable of integrating technical performance, environmental constraints, and incomplete information within a unified decision model.
This study proposes a multi-criteria optimisation methodology based on Single-Valued Trapezoidal Neutrosophic Numbers (SVTN-numbers) to support the design and operational justification of technological equipment for skidding machines in selective logging. The neutrosophic formalism enables simultaneous representation of truth, indeterminacy, and falsity components of expert evaluations, thus explicitly incorporating uncertainty inherent in forest operations. The trapezoidal structure allows interval-based modelling of key operational parameters, such as tractive effort, travel speed, and energy intensity, which are strongly influenced by slope gradient and micro-relief variability.
A decision matrix was constructed to evaluate three technological configurations for selective logging: (A1) a conventional skidder equipped with a grapple, (A2) a tractor fitted with a hydraulic manipulator, and (A3) a skidding system with a winch mounted on a front loader. Alternatives were assessed against productivity, energy consumption, and manoeuvrability in restricted stand conditions. Criteria weights were derived using a neutrosophic soft-matrix approach to reflect fluctuating external loads and partial expert knowledge. Defuzzification through a neutrosophic score function enabled the transformation of imprecise assessments into comparable scalar indicators and the identification of a Pareto-efficient solution space.
The integrated evaluation demonstrated that configuration A3 achieved the highest aggregated performance index (0.625), exceeding conventional systems (0.48 and 0.55 respectively). This result is causally associated with the structural integration of skidding and loading functions within a single machine platform. The frontal positioning of the winch improves mass distribution, enhances operational responsiveness, and reduces auxiliary handling time, thereby increasing overall system productivity while maintaining lower energy intensity per cubic metre extracted. From an environmental perspective, reduced machine passes and improved manoeuvrability contribute to decreased soil compaction risk, which is critical in selective logging systems oriented towards sustainable forest management.
The proposed neutrosophic optimisation framework transforms the parameter justification process from an intuitive engineering choice into a transparent, analytically substantiated decision-support tool. By embedding uncertainty directly into the mathematical model, it enhances the robustness of technological design under variable forest conditions. The approach provides a methodological basis for adaptive skidding machine configuration and can support strategic equipment selection in forest enterprises seeking to balance economic efficiency with ecological integrity.
| Keywords | Logging; Skidder; Neutrosophic; Optimisation |
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