A new method for intuitionistic fuzzy multi-objective linear fractional optimization problem and its application in agricultural land allocation problem

Moges, Demmelash Mollalign; Mushi, Allen; Wordofa, Berhanu

doi:10.1016/j.ins.2023.01.044

Cited by 17 publications

(23 citation statements)

References 27 publications

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“…The score functions of the membership and non-membership functions of the triangular IFN A I = a, a, a; b, a, b used in [14] are…”

Section: The Accuracy Functionmentioning

confidence: 99%

“…Any accuracy function can be used to rank the IFNs. The following three implications were used in [14]…”

Section: The Accuracy Functionmentioning

confidence: 99%

“…In this paper we analyze the shortcomings of the solution approach to intuitionistic fuzzy multiple objective linear fractional programming (IFMOLFP) problem introduced in [14]. We proceed by identifying the incorrectness in the proof of the theorem that stated the equivalence between the original IFMOLFP problem and the constructed crisp multiple objective linear fractional programming (MOLFP) problem.…”

Section: Introductionmentioning

confidence: 99%

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Enhanced Solutions to Intuitionistic Fuzzy Multiobjective Linear Fractional Optimization Problems via Lexicographic Method

Stanojević,

Pantelić,

Dzitac

2024

INT J COMPUT COMMUN, Int. J. Comput. Commun. Control

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Optimization involving fuzzy numbers generally, and intuitionistic fuzzy numbers particularly is more and more an essential part of any computational intelligence method; and might be of interest in modeling fuzzy control systems, or carrying out a fuzzy sensitivity analysis. The recent literature includes many research papers related to both theoretical modelling, and practical implementation of fuzzy decision support systems. Fuzzy optimization is one of the main part in such decisionmaking tools. A realistic solution to a fuzzy optimization problem is always desired, and similarly, a Pareto optimal solution to a multiple objective optimization problem is always a need. In this paper we analyze the shortcomings; and eliminate the weaknesses of a solution approach from the literature proposed by Moges et al. in 2023. Firstly, Moges et al. used an accuracy function to de-fuzzify the original intuitionistic fuzzy optimization problem; then linearized the obtained crisp problem; and finally involved fuzzy goals to solve the derived multiple objective linear problem. We present two faulty key points of their approach, namely the de-fuzzification and linearization steps; prove the inappropriateness of their results; and propose some improvements. The final aim in addressing the first key point is to clarify the border between defuzzifications made in accordance to true theoretical statements, and those made for modeling reasons. The methodological improvement we propose is related to the second key point and it assures that Pareto optimal solutions - highly required in multiple objective optimization - are obtained. To illustrate our point of view, we use a numerical example from the literature, and report better numerical results derived by the improved methodology.

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“…The score functions of the membership and non-membership functions of the triangular IFN A I = a, a, a; b, a, b used in [14] are…”

Section: The Accuracy Functionmentioning

confidence: 99%

“…Any accuracy function can be used to rank the IFNs. The following three implications were used in [14]…”

Section: The Accuracy Functionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Enhanced Solutions to Intuitionistic Fuzzy Multiobjective Linear Fractional Optimization Problems via Lexicographic Method

Stanojević,

Pantelić,

Dzitac

2024

INT J COMPUT COMMUN, Int. J. Comput. Commun. Control

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“…Similarly, Moges et al (2023) investigated the optimization of agricultural land allocation and proposed a novel fuzzy multi-objective programming approach. The authors employed an accuracy ranking function and variable transformation in the approach to convert the fuzzy multi-objective model into a crisp multi-objective linear optimization problem.…”

Section: Introductionmentioning

confidence: 99%

A novel optimization approach for rural development based on sustainable agriculture planning, considering the energy and water consumption nexus

Luo

Chang

Kaliyaperumal

2023

Energy Exploration & Exploitation

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In today's world, there are many changes and transformations in different sectors of the economy, and today's world economy has become more dependent on each other. The economy of many developing countries is highly dependent on agriculture. In addition, in developed countries, the agricultural sector is of special importance, so they are currently turning to the production of more organic and healthy products. One of the reasons that caused the agricultural sector to receive more attention in the economy is the existential importance of this sector in providing the raw materials of a part of the industry and the food industry needed in that country. Accordingly, in this research, the optimal cultivation pattern is determined using a linear multi-objective mathematical model, including economic, social, and environmental objectives. Moreover, the uncertainty in the input parameters of the proposed model is considered, and a robust optimization approach is applied to deal with this uncertainty. After collecting the research data for the crop year 2021-2022, the proposed robust counterpart formulation is optimized using GAMS software. The numerical results show that increasing the level of conservatism in the robust model cause to decrease in the profit of agriculture as well as increasing the total consumed water. Moreover, the results of the current research can help the decision-makers of the agricultural sector in achieving the goal of obtaining the highest profit.

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“…In their proposed problem they used ranking function for the defuzzification of fuzzy objective function and the property of equality between fuzzy numbers for the defuzzification of fuzzy constraints. El Sayed and Abo-Sinna (2021); Moges et al (2023); Malik and Gupta (2022); Niksirat (2022), etc. are the works done under fuzzy environment.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy Programming Approach to Solve Multi-Objective Fully Fuzzy Transportation Problem

Admasu Tadesse,

Sirkumar Acharya,

Berhanu Belay

2023

eajbcs

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The aim of this study is presenting the solution methodology of multi-objective fuzzy transportation problem with fuzzy decision variables, where all the input parameters and decisions variables of the programming problems are assumed to be triangular fuzzy number and triangular fuzzy decision variables respectively. Moreover the objectives under considerations are minimization of cost of transportation and minimization of shipping time under fuzzy environment. The fuzziness of the objective functions and the fuzzy constraints of the programming problem are defuzzified using the ranking function and the equality property between two fuzzy numbers, respectively. The consequent crisp multi-objective fuzzy transportation problem is tackled by employing fuzzy mathematical programming approach. Finally fuzzy decision is made after solving the resultant mathematical programming problem using LINGO(Schrage and LINDO Systems (1997)) software. Illustrative numerical example is presented in support of the proposed methodology.

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A new method for intuitionistic fuzzy multi-objective linear fractional optimization problem and its application in agricultural land allocation problem

Cited by 17 publications

References 27 publications

Enhanced Solutions to Intuitionistic Fuzzy Multiobjective Linear Fractional Optimization Problems via Lexicographic Method

Enhanced Solutions to Intuitionistic Fuzzy Multiobjective Linear Fractional Optimization Problems via Lexicographic Method

A novel optimization approach for rural development based on sustainable agriculture planning, considering the energy and water consumption nexus

Fuzzy Programming Approach to Solve Multi-Objective Fully Fuzzy Transportation Problem

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