A derivative-based algorithm for a particular class of mixed variable optimization problems

Optimization Methods and Software

Volumn 19, Issue 3-4, 2004, Pages 371-387

  Lucidi, S ^a   Piccialli, V ^a  

^a SAPIENZA UNIVERSITY OF ROME   (Italy)

Author keywords

Large scale unconstrained optimization; Mixed variable programming; Nonlinear programing

Indexed keywords

ALGORITHMS; CONVERGENCE OF NUMERICAL METHODS; FUNCTIONS; INTEGER PROGRAMMING; NUMBER THEORY; PROBLEM SOLVING;

LARGE-SCALE UNCONSTRAINED OPTIMIZATION; MIXED VARIABLE PROGRAMMING;

GLOBAL OPTIMIZATION;

EID: 3042643358     PISSN: 10556788     EISSN: None     Source Type: Journal    
DOI: 10.1080/10556780410001654197     Document Type: Conference Paper

References (9)

1. C. Audet and J.E. Dennis (2001). Pattern search algorithms for mixed variable programming. SIAM Journal on Optimization, 11, 573-594.
2. M.A. Abramson (2002). Pattern Search Algorithms for Mixed Variable General Constrained Optimization Problems. Ph.D. Thesis, Department of Computational and Applied Mathematics, Rice University, August 2002.
3. R.M. Lewis and V. Torczon (1999). Pattern search methods for bound constrained minimization. SIAM Journal on Optimization, 9(4), 1082-1099.
4. S. Lucidi, V. Piccialli and M. Sciandrone (2002). Algorithm Model for Mixed Variable Programming. Tech. Rep. DIS 17-02, University of Rome "La Sapienza".
5. C. Berge (1963). Topological Spaces. MacMillan Comp, New York.
6. D.P. Bertsekas (1982). Constrained Optimization and Lagrange Multiplier Methods. Academic Press, New York.
7. R. Dembo and T. Steihaug (1983). Truncated-Newton methods algorithms for large-scale unconstrained optimization. Mathematical Programming, 26, 190-212.
8. L. Grippo, F. Lampariello and S. Lucidi (1989). A Truncated-Newton method with nonmonotone linesearch for unconstrained optimization. J. Optim. Theory Appl., 60, 401-419.
9. L. Grippo and S. Lucidi (1997). A globally convergent version of the Polak-Ribière conjugate gradient method. Mathematical Programming, 78, 375-391.