New approach for solving intuitionistic fuzzy multi-objective transportation problem

Roy, Sankar Kumar; Ebrahimnejad, Ali; Verdegay, José L.; Das, Sukumar

doi:10.1007/s12046-017-0777-7

Cited by 67 publications

(29 citation statements)

References 32 publications

(33 reference statements)

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“…Equations (24) to (28) state that members of the supply chain that do not have any relationship will not use any transportation system. Equation (29) points out that each distribution center can only be established at a single capacity level. Equations (30) to (32) state that if one of the distributions, hybrid, or disposal centers is established in period t-1, it should be activated in the next periods.…”

Section: Physical Flow Constraintsmentioning

confidence: 99%

Multiobjective fuzzy mathematical model for a financially constrained closed‐loop supply chain with labor employment

Goli

Zare

Tavakkoli‐Moghaddam

et al. 2019

Computational Intelligence

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This paper addresses the multiobjective, multiproducts and multiperiod closed‐loop supply chain network design with uncertain parameters, whose aim is to incorporate the financial flow as the cash flow and debts' constraints and labor employment under fuzzy uncertainty. The objectives of the proposed mathematical model are to maximize the increase in cash flow, maximize the total created jobs in the supply chain, and maximize the reliability of consumed raw materials. To encounter the fuzzy uncertainty in this model, a possibilistic programming approach is used. To solve large‐sized problems, the multiobjective simulated annealing algorithm, multiobjective gray wolf optimization, and multiobjective invasive weed optimization are proposed and developed. The numerical results demonstrate that these algorithms solve the problems within about 1% of the required solving time for the augmented ε‐constraint and have similar performance and even better in some cases. The multiobjective simulated annealing algorithm with a weak performance takes less time than the other two algorithms. The multiobjective gray wolf optimization and multiobjective invasive weed optimization algorithms are superior based on the multiobjective performance indices.

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Section: Physical Flow Constraintsmentioning

confidence: 99%

Multiobjective fuzzy mathematical model for a financially constrained closed‐loop supply chain with labor employment

Goli

Zare

Tavakkoli‐Moghaddam

et al. 2019

Computational Intelligence

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“…Vincent et al [27] studied an interactive approach for the multi-objective TP with interval parameters. 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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“…Chávez et al [5], taking genuine contextual investigation, broadened a stochastic multi-objective minimum cost flow model for perishable agrarian items by comprising street transportation. As of late, Roy et al [20] examined MOTP under intuitionistic fuzzy environment.…”

Section: Literature Surveymentioning

confidence: 99%

Multi-objective stochastic transportation problem involving three-parameter extreme value distribution

Acharya

Gessesse

Mishra

et al. 2019

YUGOSLAV J OPERATION

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In this paper, we considered a multi-objective stochastic transportation problem where the supply and demand parameters follow extreme value distribution having three-parameters. The proposed mathematical model for stochastic transportation problem cannot be solved directly by mathematical approaches. Therefore, we converted it to an equivalent deterministic multi-objective mathematical programming problem. For solving the deterministic multi-objective mathematical programming problem, we used an ε-constraint method. A case study is provided to illustrate the methodology.

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New approach for solving intuitionistic fuzzy multi-objective transportation problem

Cited by 67 publications

References 32 publications

Multiobjective fuzzy mathematical model for a financially constrained closed‐loop supply chain with labor employment

Multiobjective fuzzy mathematical model for a financially constrained closed‐loop supply chain with labor employment

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

Multi-objective stochastic transportation problem involving three-parameter extreme value distribution

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