A Switching Criterion in Hybrid Quasi-Newton BFGS - Steepest Descent Direction
Two modified methods for unconstrained optimization are presented. The methods employ a hybrid descent direction strategy which uses a linear convex combination of quasi-Newton BFGS and steepest descent as search direction. A switching criterion is derived based on the First and Second order Kuhn-T...
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| Auteurs principaux: | , , |
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| Format: | Article |
| Langue: | English English |
| Publié: |
Universiti Putra Malaysia Press
1999
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| Accès en ligne: | http://psasir.upm.edu.my/id/eprint/3467/1/A_Switching_Criterion_in_Hybrid_Quasi-Newton.pdf |
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| Résumé: | Two modified methods for unconstrained optimization are presented. The methods employ a hybrid descent direction strategy which uses a linear convex
combination of quasi-Newton BFGS and steepest descent as search direction. A switching criterion is derived based on the First and Second order Kuhn-Tucker
condition. The switching criterion can be viewed as a way to change between quasi-Newton and steepest descent step by matching the Kuhn-Tucker condition. This is to ensure that no potential feasible moves away from the
current descent step to the other one that reduced the value of the objective function. Numerical results are also presented, which suggest that an improvement has been achieved compared with the BFGS algorithm. |
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