Multi-objective fixed-charge solid transportation problem with product blending under intuitionistic fuzzy environment

Roy, Sankar Kumar; Midya, Sudipta

doi:10.1007/s10489-019-01466-9

Cited by 72 publications

(28 citation statements)

References 40 publications

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“…An extension of the proposed fuzzy epsilon‐constraint method to fully intuitionistic fuzzy MOLP can be done by generalising the single‐objective case given in Reference . It is interesting to note that Roy and Midya used a linear ranking function to map each intuitionistic fuzzy number into a real number, and transformed the IFMO fixed‐charge solid transportation problem into a crisp one, which was then solved via Angelov's method .…”

Section: Concluding Remarks and Future Workmentioning

confidence: 99%

“…Thus, the obtained intuitionistic fuzzy epsilon‐constraint method could be used, for example, to solve a fully intuitionistic version of the intuitionistic fuzzy multiobjective (IFMO) fixed‐charge solid transportation problem presented by Roy and Midya . It is interesting to note that Roy and Midya used a linear ranking function to map each intuitionistic fuzzy number into a real number, and transformed the IFMO fixed‐charge solid transportation problem into a crisp one, which was then solved via Angelov's method . We have discussed on the shortcoming of such an approach for the fuzzy case.…”

Section: Concluding Remarks and Future Workmentioning

confidence: 99%

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An epsilon‐constraint method for fully fuzzy multiobjective linear programming

2020

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Linear ranking functions are often used to transform fuzzy multiobjective linear programming (MOLP) problems into crisp ones. The crisp MOLP problems are then solved by using classical methods (eg, weighted sum, epsilon‐constraint, etc), or fuzzy ones based on Bellman and Zadeh's decision‐making model. In this paper, we show that this transformation does not guarantee Pareto optimal fuzzy solutions for the original fuzzy problems. By using lexicographic ranking criteria, we propose a fuzzy epsilon‐constraint method that yields Pareto optimal fuzzy solutions of fuzzy variable and fully fuzzy MOLP problems, in which all parameters and decision variables take on LR fuzzy numbers. The proposed method is illustrated by means of three numerical examples, including a fully fuzzy multiobjective project crashing problem.

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Section: Concluding Remarks and Future Workmentioning

confidence: 99%

Section: Concluding Remarks and Future Workmentioning

confidence: 99%

An epsilon‐constraint method for fully fuzzy multiobjective linear programming

2020

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“…Roy et al [28] studied MOTP under intuitionistic fuzzy environment. Roy and Midya [29] presented a study on multi-objective fixed-charge solid transportation problem under intuitionistic fuzzy environment.…”

Section: Review Of Related Workmentioning

confidence: 99%

Time Variant Multi-Objective Interval-Valued Transportation Problem in Sustainable Development

2019

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Sustainable development is treated as the achievement of continued economic development without detriment to environmental and natural resources. Now-a-days, in a competitive market scenario, most of us are willing to pay less and to gain more in quickly without considering negative externalities for the environment and quality of life for future generations. Recalling this fact, this paper explores the study of time variant multi-objective transportation problem (MOTP) with consideration of minimizing pollution. Time of transportation is of utmost importance in reality; based on this consideration, we formulate a MOTP, where we optimize transportation time as well as the cost function. The parameters of MOTP are interval-valued, so this form of MOTP is termed as a multi-objective interval transportation problem (MOITP). A procedure is taken into consideration for converting MOITP into deterministic form and then for solving it. Goal programming is applied to solve the converted transportation problem. A case study is conducted to justify the methodology by utilizing the environmental impact. At last, conclusions and future research directions are included regarding our study.

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“…They used the constraint method to find a Pareto solution. Furthermore, Roy and Midya investigated such problem under fuzzy environment. They applied a new ranking method to convert the fuzzy counterpart to a deterministic form.…”

Section: Literature Reviewmentioning

confidence: 99%

A multiobjective integrated multiproject scheduling and multiskilled workforce assignment model considering learning effect under uncertainty

Hematian

Esfahani

Mahdavi

et al. 2019

Computational Intelligence

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Today, organizations try to decline academically expenses using humans and resources in addition to rising managers and operators' satisfaction. Meantime, a very important step in the process of decision is the assignment of human resources, particularly in connection with research and development (R&D) projects in which the system is highly dependent on the capabilities of human resources. In this study, we tried all the assumptions that come true in the real world, considered a model for applied R&D projects to reduce costs and increase the efficiency of projects. Therefore, an integrated multiproject scheduling and multiskill human resource assignment model under uncertainty has developed for R&D projects. Furthermore, it is assumed that the activity processing time is related to human resources assignment that means the learning effect is considered. To demonstrate the proposed model efficiency, the various dimensions instance problem was solved accurately and efficiently in GAMS software, and the results have been reported. In addition, the proposed model is validated through the input parameter sensitivity analysis. The results indicate a suitable performance of the proposed fuzzy mathematical programming model is due to the complexity of the problem.

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Multi-objective fixed-charge solid transportation problem with product blending under intuitionistic fuzzy environment

Cited by 72 publications

References 40 publications

An epsilon‐constraint method for fully fuzzy multiobjective linear programming

An epsilon‐constraint method for fully fuzzy multiobjective linear programming

Time Variant Multi-Objective Interval-Valued Transportation Problem in Sustainable Development

A multiobjective integrated multiproject scheduling and multiskilled workforce assignment model considering learning effect under uncertainty

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