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A Wolfe-Type Steepest Descent Algorithm for Uncertain Quadratic Multiobjective Optimization Problems
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DOI：10.5269/bspm.81660.png)
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Abstract
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This work develops a Wolfe-type steepest descent algorithm for solving uncertain quadratic multiobjective optimization problems (UQMOPs) by reformulating them into deterministic robust counterparts via objective-wise worst-case criteria. The proposed method incorporates a Wolfe-type inexact line search to obtain more efficient descent directions and improve overall convergence behavior. A Zoutendijk-type condition is established to guarantee linear convergence under standard assumptions.
Keywords:
Quadratic problem
uncertainty
multiobjective optimization
robust efficiency
steepest descent method
Journal
B
IF:
0.4
Papers:
604
Citations:
0
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