What is it about?
This paper deals with constrained multi-stage machines flow shop (FS) Scheduling model in which processing times, job weights, and break-down machine time are characterized by fuzzy numbers that are piecewise as well as quadratic in nature. Avoiding to convert the model into its crisp, the closed interval approximation for the piecewise quadratic fuzzy numbers is incorporated.
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Why is it important?
The suggested method leads to an optimal sequence to the considered problem which is a non-crossing optimal sequence and minimizing the total elapsed time under fuzziness.
Perspectives
The proposed approach helps the decision maker to search for finding applicable solution related to real world problems and minimizes the total fuzzy elapsed time. A numerical example is provided for the illustration of the suggested methodology.
Dr. PAVAN KUMAR
VIT Bhopal University
Read the Original
This page is a summary of: Enhancement of Capacitated Transportation Problem in Fuzzy Environment, Advances in Fuzzy Systems, October 2020, Hindawi Publishing Corporation,
DOI: 10.1155/2020/8893976.
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Resources
Solving constrained flow shop scheduling problem through multi- stage fuzzy binding approach with fuzzy due dates
This paper deals with constrained multi-stage machines flow shop (FS) Scheduling model in which processing times, job weights, and break-down machine time are characterized by fuzzy numbers that are piecewise as well as quadratic in nature. Avoiding to convert the model into its crisp, the closed interval approximation for the piecewise quadratic fuzzy numbers is incorporated. The suggested method leads to an optimal sequence to the considered problem which is a non-crossing optimal sequence and minimizing the total elapsed time under fuzziness. The proposed approach helps the decision maker to search for finding applicable solution related to real world problems and minimizes the total fuzzy elapsed time. A numerical example is provided for the illustration of the suggested methodology.
Enhancement of Capacitated Transportation Problem in Fuzzy Environment
This research work aims to study a capacitated transportation problem (CTP) with penalty cost, supplies, and demands represented by hexagonal fuzzy numbers. Based on ranking function, the supplies and demands are converted to the crisp form. Through the use of the level, the problem is converted into interval linear programming. To optimize the interval objective function, we define the order relations represented by policy maker’s choice between intervals. The maximization (minimization) problem considering the interval objective function is transformed to multiobjective optimization problem based on order relations introduced by the preference of policy makers between interval profits (costs). A numerical example is given for illustration and to check the validity of the suggested approach.
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