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On the convergence of conditional gradient method for unbounded multiobjective optimization problems
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DOI：10.1016/j.orl.2025.107366.png)
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Abstract
En 中文
This paper focuses on developing the conditional gradient algorithm with adaptive step size for multiobjective optimization problems on unbounded feasible regions. By employing the recession cone, we establish the welldefined nature of the algorithm. Under mild assumptions, we obtain the asymptotic convergence property and the iteration-complexity bound. Furthermore, a new variant of the algorithm is proposed, and the rate of convergence of this variant is obtained. Numerical experiments are conducted to verify the performance of the algorithms.
Keywords:
Multiobjective optimization
Unbounded constraint
Conditional gradient method
Recession cone
Convergence
Journal
O
IF:
0.9
Papers:
52
Citations:
3.5K
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