论文信息 - A Levenberg-Marquardt algorithm for unconstrained multicriteria optimization

A Levenberg-Marquardt algorithm for unconstrained multicriteria optimization

To compute one of the nonisolated Pareto-critical points of an unconstrained multicriteria optimization problem a Levenberg-Marquardt algorithm is applied. Sufficient conditions for an error bound are provided to prove its fast local convergence. A globalized version is shown to converge to a Pareto-optimal point under convexity assumptions.

Andreas Fischer | Pradyumn Kumar Shukla | A. Fischer | P. Shukla

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