An infeasible-interior-point algorithm using projections onto a convex set

Conference · Sat Dec 31 04:00:00 EST 1994

OSTI ID:36290

Mizuno, S; Jarre, F

We present a new class of primal-dual infeasible-interior-point methods for solving linear programs. The iterates generated by our methods lie in the positive orthant and are not restricted elsewhere. Our methods comprise the following features: At each step a projection is used to {open_quotes}recenter{close_quotes} the variables to the domain x{sub i}s{sub i} {>=} {mu}. The projections are separable into two-dimensional orthogonal projections on a convex set, and thus they are easy to implement. The use of orthogonal projections allows that a full Newton step can be taken at each iteration, even if the result violates the nonnegativity condition. We prove that a short step version of our method converges in polynomial time.

• OSTI ID: 36290
• Report Number(s): CONF-9408161--
• Country of Publication: United States
• Language: English

Related Subjects

99 GENERAL AND MISCELLANEOUS
ACCURACY
ALGORITHMS
CONVERGENCE
MATRICES
NUMERICAL SOLUTION
OPTIMIZATION
VARIATIONAL METHODS