Parametric approach to quadratically constrained multi-level multi-objective quadratic fractional programming

The paper proposed a method to study and obtain a set of Pareto optimal solutions or a set of representative solutions to a quadratically constrained multi-level multiobjective quadratic fractional programming problem. This problem involves several objectives to be fulfilled at multi levels under a...

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Vydané v:Opsearch Ročník 58; číslo 3; s. 557 - 574
Hlavní autori: Goyal, Vandana, Rani, Namrata, Gupta, Deepak
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: New Delhi Springer India 01.09.2021
Springer Nature B.V
Predmet:
Algorithms
Business and Management
Constraints
Decision making
Equivalence
Management
Mathematical programming
Mathematics
Operations research
Operations Research/Decision Theory
Parametric statistics
Theoretical Article
Constraint method
Multi-level multiobjective quadratic fractional programming (MLMOQFP)
Parametric approach
Parametric vector
ISSN:0030-3887, 0975-0320
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Shrnutí:The paper proposed a method to study and obtain a set of Pareto optimal solutions or a set of representative solutions to a quadratically constrained multi-level multiobjective quadratic fractional programming problem. This problem involves several objectives to be fulfilled at multi levels under a common set of quadratic constraints. Initially, we used parametric approach to convert the fractional programming model to an equivalent non-fractional programming model by allocating a parametric vector to each fractional objective. Then, ε -constraint method is used to convert this multiobjective programming model into an equivalent model with single objective. The solution of every previous level is followed by the next level in succession to find a solution which is suitable to each level decision maker. An algorithm and numerical example are also presented at the end of the paper to validate the proposed methodology for the Model.
Bibliografia:ObjectType-Article-1
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content type line 14
ISSN:0030-3887
0975-0320
DOI:10.1007/s12597-020-00497-y