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Fuzzy programming for multi-choice bilevel transportation problem

100%
ARORA R., GUPTA K.
Operations Research and Decisions
|
2021
|
vol. 31
|
issue 3
5-21
XX
Multi-choice programming problems arise due to the diverse needs of people. In this paper, multi-choice optimization has been applied to the bilevel transportation problem. This problem deals with transportation at both the levels, upper as well as lower. There are multiple choices for demand and supply parameters. The multi-choice parameters at the respective levels are converted into polynomials which transmute the defined problem into a mixed integer programming problem. The objective of the paper is to determine a solution methodology for the transformed problem. The significance of the formulated model is exhibited through an example by applying it to the hotel industry. The fuzzy programming approach is employed to obtain a satisfactory solution for the decision-makers at the two levels. A comparative analysis is presented in the paper by solving the bilevel multi-choice transportation problem with goal programming mode as well as by the linear transformation technique. The example is solved using computing software.
2
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Branch and bound algorithm for discrete multi- level linear fractional programming problem

100%
ARORA R., GUPTA K.
Operations Research and Decisions
|
2018
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vol. 28
|
issue 2
5-21
EN
An algorithm is proposed to find an integer solution for bilevel linear fractional programming problem with discrete variables. The method develops a cut that removes the integer solutions which are not bilevel feasible. The proposed method is extended from bilevel to multilevel linear fractional programming problems with discrete variables. The solution procedure for both the algorithms is elucidated in the paper.
3
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Optimization of an EPQ model in an imprecise environment with defuzzification by the centroid method under inflation

81%
ARORA R., CHAUHAN A., SHARMA R., SINGH A. P.
Operations Research and Decisions
|
2022
|
vol. 32
|
issue 3
32-48
EN
The awareness of making decisions in an imprecise environment has resulted in considering the inventory system under a fuzzy approach. The effects of uncertain demand have been finding increased application in many inventory systems. Un-certainty creates complicated situations for the manufacturer in making decisions. Markets have become more competitive as a result of technological advancements. The effect of inflation on the overall cost of the inventory system is useful in providing a tool for the analysis of inventory decisions. This study intended to estimate the effect of different fuzzy numbers on a manufacturer's annual joint expected total cost. The comparative study of this proposed model has been considered for two different fuzzy numbers with the defuzzification technique as the centroid method. The optimization technique has been used to minimize the producer’s joint expected total cost under the condition mentioned earlier, and the model is validated numerically.
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