Superposition relaxation creates separable estimators for factorable functions that are tighter than McCormick relaxations in numerical tests while providing convergence guarantees.
Springer, Berlin, Germany (2011)
2 Pith papers cite this work, alongside 1,440 external citations. Polarity classification is still indexing.
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The paper shows isolated calmness of the Lagrange multiplier mapping is sufficient for the Robinson-Zowe-Kurcyusz constraint qualification and equivalent to the strict version under extra assumptions, with examples.
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Relaxation via Separable Estimators: Arithmetic and Implementation
Superposition relaxation creates separable estimators for factorable functions that are tighter than McCormick relaxations in numerical tests while providing convergence guarantees.
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Uniqueness and stability of Lagrange multipliers and associated qualification conditions
The paper shows isolated calmness of the Lagrange multiplier mapping is sufficient for the Robinson-Zowe-Kurcyusz constraint qualification and equivalent to the strict version under extra assumptions, with examples.