Novel multi-objective, multi-item and four-dimensional transportation problem with vehicle speed in LR-type intuitionistic fuzzy environment

Samanta, Sasmita; Jana, Dipak Kumar; Panigrahi, Goutam; Maiti, Manoranjan

doi:10.1007/s00521-019-04675-y

Cited by 23 publications

(7 citation statements)

References 26 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Additionally, they asserted that this method is concerned with optimizing the acceptance level of objective functions while minimizing the deviational variables associated with each goal. Samanta et al (2020) presented four-dimensional TP in LR (left and right)-type IFSs. They also specified the speed of various vehicles and the rate of speed disruption caused by the road conditions on various routes to achieve the time minimization aim.…”

Section: Solid Transportation Problems Under Uncertain Environmentsmentioning

confidence: 99%

See 1 more Smart Citation

A parametric neutrosophic model for the solid transportation problem

Yuanxiang

Uluçay

2022

View full text Add to dashboard Cite

PurposeThis research attempts to present a solid transportation problem (STP) mechanism in uncertain and indeterminate contexts, allowing decision makers to select their acceptance, indeterminacy and untruth levels.Design/methodology/approachDue to the lack of reliable information, changeable economic circumstances, uncontrolled factors and especially variable conditions of available resources to adapt to the real situations, the authors are faced with a kind of uncertainty and indeterminacy in constraints and the nature of the parameters of STP. Therefore, an approach based on neutrosophic logic is offered to make it more applicable to real-world circumstances. In this study, the triangular neutrosophic numbers (TNNs) have been utilized to represent demand, transportation capacity, accessibility and cost. Then, the neutrosophic STP was converted into an interval programming problem with the help of the variation degree concept. Then, two simple linear programming models were extracted to obtain the lower and upper bounds of the optimal solution.FindingsThe results reveal that the new model is not complicated but more flexible and more relevant to real-world issues. In addition, it is evident that the suggested algorithm is effective and allows decision makers to specify their acceptance, indeterminacy and falsehood thresholds.Originality/valueUnder the transportation literature, there are several solutions for TP and STP in crisp, fuzzy set (FS) and intuitionistic fuzzy set (IFS) conditions. However, the STP has never been explored in connection with neutrosophic sets to the best of the authors’ knowledge. So, this work tries to fill this gap by coming up with a new way to solve this model using NSs.

show abstract

Section: Solid Transportation Problems Under Uncertain Environmentsmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

A parametric neutrosophic model for the solid transportation problem

Yuanxiang

Uluçay

2022

View full text Add to dashboard Cite

show abstract

“…In some cases, transportation problems have more than one objective function, for example the time and cost functions will be optimized simultaneously. Transportation problems with more than one objective function are called multiobjective transportation problems (Kakran & Dhodiya, 2020), (Bagheri et al, 2020), (Gowthami & Prabakaran, 2019), (Samanta et al, 2020), (Roy et al, 2018).…”

Section: Introduction *mentioning

confidence: 99%

“…The convex combination method can be used. Convex combination is a concept programming method used to achieve Pareto optimal solutions of uncertain multi objective programming problems (Dalman, 2018), (Samanta et al, 2020). The optimal solution with the convex combination method is influenced by the determination of the weight values in the objective function.…”

Section: Introduction *mentioning

confidence: 99%

Convex Combination Method on Probabilistic Fuzzy Multiobjective Transportation Problem with Pareto Distribution

et al. 2022

View full text Add to dashboard Cite

This article introduces a transportation model with two objective functions. The first objective function is the function which minimizes the total cost and the second objective function is the function which minimizes the total time. Parameters of source, destination and maximum capacity of transportation means are assumed to follow the Pareto distribution. The multiobjective transportation model is the development of a single objective transportation model. Parameters of the objective function are expressed by triangular fuzzy numbers. Fuzzy multi objective problems are transformed into a deterministic single objective using the convex combination method. The formulated model is applied to the problem of shipping metal crates. There are 3 types of conveyances namely HDL, Engkel and Wingbox. Obtained the optimal total cost of Rp. 3,770,294 and metal crates delivery time to be for 13 hours.

show abstract

“…Before formulating the problem of concern, we realized that under distinct situations, all previous work was formulated for the problem of production and transportation. Samanta et al [27] formulated multi-objective and multiitem TP with ambiguity, and also implemented the speed of various vehicles and traffic disruption factor for the time minimization for the first time owing to the road conditions on different roads. Kaushal et al [28] developed a hierarchical design model of fixed charge fractional TP for a food chain business in which the organic cooking oil used for processing.…”

Section: Introductionmentioning

confidence: 99%

Parameter estimation and optimization of multi-objective capacitated stochastic transportation problem for gamma distribution

Gupta

Garg

Chaudhary

2020

Complex Intell. Syst.

View full text Add to dashboard Cite

The transportation problem in real life is an uncertain problem with multi-objective decision-making. In particular, by considering the conflicting objectives/criteria such as transportation costs, transportation time, discount costs, labour costs, damage costs, decision maker searches for the best transportation setup to find out the optimum shipment quantity subject to certain capacity restrictions on each route. In this paper, capacitated stochastic transportation problem is formulated as a multi-objective optimization model along with some capacitated restrictions on the route. In the formulated problem, we assume that parameters of the supply and demand constraints' follow gamma distribution, which is handled by the chance constrained programming approach and the maximum likelihood estimation approach has been used to assess the probabilistic distributions of the unknown parameters with a specified probability level. Furthermore, some of the objective function's coefficients are consider as ambiguous in nature. The ambiguity in the formulated problem has been presented by interval type 2 fuzzy parameter and converted into the deterministic form using an expected value function approach. A case study on transportation illustrates the computational procedure.

show abstract

Novel multi-objective, multi-item and four-dimensional transportation problem with vehicle speed in LR-type intuitionistic fuzzy environment

Cited by 23 publications

References 26 publications

A parametric neutrosophic model for the solid transportation problem

A parametric neutrosophic model for the solid transportation problem

Convex Combination Method on Probabilistic Fuzzy Multiobjective Transportation Problem with Pareto Distribution

Parameter estimation and optimization of multi-objective capacitated stochastic transportation problem for gamma distribution

Contact Info

Product

Resources

About