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An efficient gradient method using the Yuan steplength

Asmundis, Roberta De; Serafino, Daniela di; Hager, William - In: Computational Optimization and Applications 59 (2014) 3, pp. 541-563

We propose a new gradient method for quadratic programming, named SDC, which alternates some steepest descent (SD) iterates with some gradient iterates that use a constant steplength computed through the Yuan formula. The SDC method exploits the asymptotic spectral behaviour of the Yuan...

Persistent link: https://www.econbiz.de/10011151838

A genetic algorithm for a global optimization problem arising in the detection of gravitational waves

Serafino, Daniela di; Gomez, Susana; Milano, Leopoldo; … - In: Journal of Global Optimization 48 (2010) 1, pp. 41-55

Persistent link: https://www.econbiz.de/10008673942

GRASP with Path Relinking for Three-Index Assignment

Aiex, Renata M.; Resende, Mauricio G.C.; Pardalos, Panos M. - In: INFORMS journal on computing : JOC 17 (2005) 2, pp. 224-247

Persistent link: https://www.econbiz.de/10007098456

A genetic algorithm for a global optimization problem arising in the detection of gravitational waves

di Serafino, Daniela; Gomez, Susana; Milano, Leopoldo; … - In: Journal of global optimization : an international … 48 (2010) 1, pp. 41-56

Persistent link: https://www.econbiz.de/10008443658

Ellipsoidal Approach to Box-Constrained Quadratic Problems

de Angelis, Pasquale L.; Bomze, Immanuel M.; Toraldo, … - In: Journal of global optimization : an international … 28 (2004) 1, pp. 1-16

Persistent link: https://www.econbiz.de/10007155812