Decision making model in forest road network management

Abstract

Forest resource exploitation and the achievement of full forest potential depend on the density and quality of the forest road network. The forest road network has to fulfill multiple functions; it thus has strategic importance in forest management. When planning the forest road network development, decision makers have to consider various technological, economic, social, and environmental factors. A comprehensive and functional approach is needed. A hybrid methodological framework for the formulation of guidelines, within which the strategy for the development of the state-owned forest road network should be defined, is presented in this paper. A fuzzy modification of the A'WOT method is proposed. The model, named FDA'WOT model, is based on an idea to provide a conceptual framework for strategic option selection by combining the fuzzy Delphi technique, the fuzzy SWOT analysis (Strengths, Weaknesses, Opportunities, Threats) and the Analytical Hierarchical Process (AHP). The FDA'WOT model overcomes the problems of a classical SWOT analysis related to the vagueness and uncertainties in assessment of the character, impact and relative importance of strategic factors. It is a frame for a multicriteria approach in decision making which allows analytical prioritization of alternative strategic options and selection of an optimal one. The proposed model is applied to a case study of the strategy selection for the forest road network development in the Republic of Serbia. The presented results have shown that the FDA'WOT model can successfully create conditions for sustainable strategy formulation.

Evaluation of Human Resources in Transportation Companies Using Multi-Criteria Model for Ranking Alternatives by Defining Relations between Ideal and Anti-Ideal Alternative (RADERIA)

“…The LBWA model is used for expressing real relations among criteria, without approximations of the expert judgments. Moreover, the LBWA model eliminates deviations of expert judgments that appear after using scales with a small range of values [37]. By eliminating this kind of problem, we also eliminate the approximation of expert judgments.…”

“…We emphasize this because when increasing the level of consistency in the AHP and the BWM, expert judgments are distorted as a result of the violation of the consistency of the model. The mentioned problem is often due to the use of the nine-point scale, which has limited possibilities for expressing expert judgments [37]. The LBWA model has the following advantages: (1) enables rationally expressing the judgments of a decision-maker with a minimal number of comparisons, n − 1; (2) eliminates the shortcomings of nine-point that are described in many studies (Asadabadi et al, 2019); and (3) the shown model has great flexibility while expressing expert judgments and it eliminates discrepancies which can occur with models that use the pairwise comparison technique.…”

Cloud-Based Multi-Robot Path Planning in Complex and Crowded Environment Using Fuzzy Logic and Online Learning

“…Fuzzy logic techniques are efficient in solving complex, ill-defined problems that are characterized by uncertainty of environment and fuzziness of information [36,37]. Taking into account that disturbances and noises are common sources of uncertainties, it can be concluded that from the aspect of fuzzy implementation this system is highly resistant to noise and disturbance [38,39,40]. The fuzzy membership functions for the input linguistic variables, as well as the output linguistic variable are given in Figure 6.…”