Optimization for multi-objective sum of linear and linear fractional programming problem: fuzzy nonlinear programming approach

Multi-objective linear plus linear fractional programming problem is an emerging tool for solving problems in different environments such as production planning, financial and corporate planning and healthcare and hospital planning which has attracted many researchers in recent years. This paper pre...

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Veröffentlicht in:Mathematical sciences (Karaj, Iran) Jg. 14; H. 3; S. 219 - 233
Hauptverfasser: Veeramani, C., Sharanya, S., Ebrahimnejad, Ali
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Berlin/Heidelberg Springer Berlin Heidelberg 01.09.2020
Springer Nature B.V
Schlagworte:
Applications of Mathematics
Approximation
Corporate planning
Euclidean geometry
Goal programming
Linear programming
Mathematical programming
Mathematics
Mathematics and Statistics
Multiple objective analysis
Nonlinear programming
Optimization
Original Research
Problem solving
Production planning
Linear programming problem
Multi-objective linear plus linear fractional programming problem
Goal programming
Multi-objective nonlinear programming problem
ISSN:2008-1359, 2251-7456
Online-Zugang:Volltext
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Zusammenfassung:Multi-objective linear plus linear fractional programming problem is an emerging tool for solving problems in different environments such as production planning, financial and corporate planning and healthcare and hospital planning which has attracted many researchers in recent years. This paper presents a method to find a Pareto optimal solution for the multi-objective linear plus linear fractional programming problem through nonlinear membership function. The proposed approach defines a fuzzy goal for each objective through a nonlinear membership function. By means of nonlinear membership function, the multi-objective linear plus linear fractional programming problem transformed into a multi-objective nonlinear programming problem. Applying the linear approximation method, the nonlinear objectives are converted into linear. In order to solve the multi-objective linear programming problem, the fuzzy goal programming model is formulated by minimizing the negative deviational variables. The proposed procedure is illustrated through numerical examples and a real-life application problem. Further, it is compared with the existing methods. Finally, the Euclidean distance function has been used to prove the efficiency of the proposed method.
Bibliographie:ObjectType-Article-1
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content type line 14
ISSN:2008-1359
2251-7456
DOI:10.1007/s40096-020-00333-w