The existed regional green manufacturing level assessment methods pay little attention to the multi-source information such as the expert's psychological preference information, the preference information among re...
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The existed regional green manufacturing level assessment methods pay little attention to the multi-source information such as the expert's psychological preference information, the preference information among regions, the heterogeneous information of regions on attributes and the interactions information between attributes at the same time, which is as a heterogeneous multi-attribute decision making (MADM) problems. A novel intuitionistic fuzzy goal programming is proposed for HMADM problems under multi-source information. The Choquet integral-based relative ratio is proposed on the basis of the Choquet integral measure. It is far away from the negative-ideal solution (NIS) and closeness to the positive-ideal solution (NIS) simultaneously with the interactions between attributes. Hereby the consistency and inconsistency indices with expert's hesitation degrees are defined, the attribute weights are solved by using the developed intuitionistic fuzzy goal programming models with the optimistic, pessimistic and mixed methods. The Choquet integral-based relative ratios of alternatives can be calculated to generate their ranking orders. Finally, a regional green manufacturing level assessment example and compared with existed methods show that the superiority and validity of the proposed method, which improves the intuitionistic fuzzy goal programming methods, LINMAP methods and MADM methods with the interactions between attributes.
This paper presents a two-phase intuitionistic fuzzy goal programming (two-phase IFGP) algorithm to solve Multi-Objective Multilevel programming (MO-MLP) problems. The coefficient of each objective and constraint func...
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This paper presents a two-phase intuitionistic fuzzy goal programming (two-phase IFGP) algorithm to solve Multi-Objective Multilevel programming (MO-MLP) problems. The coefficient of each objective and constraint function is assumed to be triangular intuitionisticfuzzy parameters and the crisp MO-MLP problems are obtained using the accuracy function method. To avoid decision lock, the top levels set tolerance limits for decision variables to control the lower levels. The problem is modeled in the intuitionisticfuzzy environment using membership and non-membership functions for each objective function at all levels and decision variables controlled by the top levels. Then, we proposed an IFGP algorithm to achieve the highest degree of each membership and non-membership goal by minimizing unwanted deviational variables and generating compensatory solutions for all decision-makers at all levels. Moreover, in the proposed approach, two-phase IFGP is modeled to yield a compromise solution that satisfies both the MN-Pareto optimal solution and the Pareto optimal solution at each level. Also, verification of the proposed method is discussed with numerical examples.
This paper presents a new method for solving an intuitionisticfuzzy multi-objective linear fractional optimization (IFMOLFO) problem with crisp and intuitionisticfuzzy constraints. Here, all uncertain parameters are...
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This paper presents a new method for solving an intuitionisticfuzzy multi-objective linear fractional optimization (IFMOLFO) problem with crisp and intuitionisticfuzzy constraints. Here, all uncertain parameters are represented as triangular intuitionisticfuzzy numbers. We used an accuracy ranking function and variable transformation in the proposed method to convert an IFMOLFO problem into a crisp multi-objective linear optimization problem. Then, we formulated the first phase of the weighted intuitionistic fuzzy goal programming (WIFGP) model to obtain an intuitionisticfuzzy non-dominant (IFND) solution for the IFMOLFO problem. Several strategies for obtaining an IFND solution to the IFMOLFO prob-lem have been proposed in the literature. However, in addition to constructing the phase-I WIFGP model, this study shows that the IFND solution may not be Pareto-optimal when some of the under-deviation variables are zero. As a result, the second phase of the WIFGP model is applied to address this issue. The benefits of both models are merged to provide a novel method, unlike any other method in the literature, for producing optimal solutions that satisfy both IFND and Pareto-optimal requirements. The suggested algo-rithm's efficiency and reliability are demonstrated by addressing a real-life case study of an agricultural production planning problem and followed by solving a numerical example from literature.(c) 2023 Elsevier Inc. All rights reserved.
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