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Sustainable forest resources management model through Pythagorean fuzzy MEREC–MARCOS approach.

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Title: Sustainable forest resources management model through Pythagorean fuzzy MEREC–MARCOS approach.
Authors: Mondal, M. K.1 (AUTHOR) manojmondol@gmail.com, Mahapatra, B. S.1 (AUTHOR) biplab.22@gmail.com, Bera, M. B.1 (AUTHOR) mihirmath2005@gmail.com, Mahapatra, G. S.2 (AUTHOR) gsmahapatra@yahoo.com
Source: Environment, Development & Sustainability. Feb2026, Vol. 28 Issue 2, p4991-5022. 32p.
Subject Terms: *Forest management, *Multiple criteria decision making, *Forest dynamics, *Forest productivity, *Fuzzy sets, *Environmental policy
Abstract: This article aims to establish a sustainable, steady-state forest that can provide ongoing environmental and economic benefits. A sustainable forest management model (SFMM) must be established to achieve this objective, incorporating a systematic policy to deal with environmental factors, forest ecosystem dynamics, human factors, and several others. This paper develops SFMMs that integrate multiple objectives, such as maximizing wood production, maximizing landscape diversity, and transforming into regulated forests. Eight SFMMs are constructed focusing on four objectives and two types of period length. Four distinct edge classes are considered for each criterion: timber volume during the conversion period, wood output during the final phase, and harvesting cost. The cost of re-planting is also considered a crucial criterion for model construction. The qualitative nature of the SFMMs' criteria is quantified using triangular Pythagorean fuzzy numbers. We propose a Pythagorean extension of the Method Based on the Removal Effects of criterion (MEREC) to find the fuzzy weights of the criterion to overcome the decision-maker's lack of knowledge in calculating the criteria weight. Along with these fuzzy weights, we developed Pythagorean measurement alternatives and ranking according to compromise solution (MARCOS) approach to solve uncertain MCDM issues. The integrated Pythagorean MEREC–MARCOS technique is then used to rank the SFMMs. The proposed approach is compared to existing crisp methodologies to demonstrate merit and consistency. The sensitivity analysis involves using rank-sum and rank-exponent techniques to ascertain the criteria weights, hence establishing the ranking of the SFMMs. Also, several closeness parameters are used to analyze the behaviour of the suggested approach in order to assist the decision-maker. The first model, which has a ten-year periodic length, achieves the highest level of acceptance. The objective of "maximize the total volume produced throughout the planning period" is essential in determining the ranking of SFMMs. The seventh model, with its six-year cycles and goal of maximizing landscape diversity, has the lowest level of acceptance. The objectives for constructing SFMMs are more crucial than the periodic length when determining ranking. This article is a first attempt at applying the Pythagorean MARCOS method to determine the best SFMM. Also, the fuzzy criteria weights are, for the first time, derived by the Pythagorean MEREC approach. [ABSTRACT FROM AUTHOR]
Database: Energy & Power Source
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  Data: Sustainable forest resources management model through Pythagorean fuzzy MEREC–MARCOS approach.
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  Data: <searchLink fieldCode="AR" term="%22Mondal%2C+M%2E+K%2E%22">Mondal, M. K.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> manojmondol@gmail.com</i><br /><searchLink fieldCode="AR" term="%22Mahapatra%2C+B%2E+S%2E%22">Mahapatra, B. S.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> biplab.22@gmail.com</i><br /><searchLink fieldCode="AR" term="%22Bera%2C+M%2E+B%2E%22">Bera, M. B.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> mihirmath2005@gmail.com</i><br /><searchLink fieldCode="AR" term="%22Mahapatra%2C+G%2E+S%2E%22">Mahapatra, G. S.</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> gsmahapatra@yahoo.com</i>
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  Data: <searchLink fieldCode="JN" term="%22Environment%2C+Development+%26+Sustainability%22">Environment, Development & Sustainability</searchLink>. Feb2026, Vol. 28 Issue 2, p4991-5022. 32p.
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  Data: *<searchLink fieldCode="DE" term="%22Forest+management%22">Forest management</searchLink><br />*<searchLink fieldCode="DE" term="%22Multiple+criteria+decision+making%22">Multiple criteria decision making</searchLink><br />*<searchLink fieldCode="DE" term="%22Forest+dynamics%22">Forest dynamics</searchLink><br />*<searchLink fieldCode="DE" term="%22Forest+productivity%22">Forest productivity</searchLink><br />*<searchLink fieldCode="DE" term="%22Fuzzy+sets%22">Fuzzy sets</searchLink><br />*<searchLink fieldCode="DE" term="%22Environmental+policy%22">Environmental policy</searchLink>
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  Label: Abstract
  Group: Ab
  Data: This article aims to establish a sustainable, steady-state forest that can provide ongoing environmental and economic benefits. A sustainable forest management model (SFMM) must be established to achieve this objective, incorporating a systematic policy to deal with environmental factors, forest ecosystem dynamics, human factors, and several others. This paper develops SFMMs that integrate multiple objectives, such as maximizing wood production, maximizing landscape diversity, and transforming into regulated forests. Eight SFMMs are constructed focusing on four objectives and two types of period length. Four distinct edge classes are considered for each criterion: timber volume during the conversion period, wood output during the final phase, and harvesting cost. The cost of re-planting is also considered a crucial criterion for model construction. The qualitative nature of the SFMMs' criteria is quantified using triangular Pythagorean fuzzy numbers. We propose a Pythagorean extension of the Method Based on the Removal Effects of criterion (MEREC) to find the fuzzy weights of the criterion to overcome the decision-maker's lack of knowledge in calculating the criteria weight. Along with these fuzzy weights, we developed Pythagorean measurement alternatives and ranking according to compromise solution (MARCOS) approach to solve uncertain MCDM issues. The integrated Pythagorean MEREC–MARCOS technique is then used to rank the SFMMs. The proposed approach is compared to existing crisp methodologies to demonstrate merit and consistency. The sensitivity analysis involves using rank-sum and rank-exponent techniques to ascertain the criteria weights, hence establishing the ranking of the SFMMs. Also, several closeness parameters are used to analyze the behaviour of the suggested approach in order to assist the decision-maker. The first model, which has a ten-year periodic length, achieves the highest level of acceptance. The objective of "maximize the total volume produced throughout the planning period" is essential in determining the ranking of SFMMs. The seventh model, with its six-year cycles and goal of maximizing landscape diversity, has the lowest level of acceptance. The objectives for constructing SFMMs are more crucial than the periodic length when determining ranking. This article is a first attempt at applying the Pythagorean MARCOS method to determine the best SFMM. Also, the fuzzy criteria weights are, for the first time, derived by the Pythagorean MEREC approach. [ABSTRACT FROM AUTHOR]
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RecordInfo BibRecord:
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      – Type: doi
        Value: 10.1007/s10668-024-05164-6
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      – Code: eng
        Text: English
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        PageCount: 32
        StartPage: 4991
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      – SubjectFull: Forest management
        Type: general
      – SubjectFull: Multiple criteria decision making
        Type: general
      – SubjectFull: Forest dynamics
        Type: general
      – SubjectFull: Forest productivity
        Type: general
      – SubjectFull: Fuzzy sets
        Type: general
      – SubjectFull: Environmental policy
        Type: general
    Titles:
      – TitleFull: Sustainable forest resources management model through Pythagorean fuzzy MEREC–MARCOS approach.
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            NameFull: Mondal, M. K.
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            NameFull: Mahapatra, B. S.
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            NameFull: Bera, M. B.
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            – D: 01
              M: 02
              Text: Feb2026
              Type: published
              Y: 2026
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              Value: 28
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            – TitleFull: Environment, Development & Sustainability
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