- Interior point method
Interior point methods (also referred to as barrier methods) are a certain class of
algorithm s to solve linear and nonlinearconvex optimization problems.These algorithms have been inspired by
Karmarkar's algorithm , developed byNarendra Karmarkar in 1984 forlinear programming . The basic elements of the method consists of aself-concordant barrier function used to encode theconvex set . Contrary to the simplex method, it reaches an optimal solution by traversing the interior of the feasible region.Any convex optimization problem can be transformed into minimizing (or maximizing) a
linear function over a convex set. The idea of encoding the feasible set using a barrier and designing barrier methods was studied in the early 1960s by, amongst others, Anthony V. Fiacco and Garth P. McCormick. These ideas were mainly developed for generalnonlinear programming , but they were later abandoned due to the presence of more competitive methods for this class of problems (e.g.sequential quadratic programming ).Yurii Nesterov and Arkadii Nemirovskii came up with a special class of such barriers that can be used to encode any convex set. They guarantee that the number of
iteration s of the algorithm is bounded by a polynomial in the dimension and accuracy of the solution.Karmarkar's breakthrough revitalized the study of interior point methods and barrier problems, showing that it was possible to create an
algorithm for linear programming characterized by polynomial complexity and, moreover, that was competitive with the simplex method.Already Khachiyan'sellipsoid method was a polynomial time algorithm; however, in practice it was too slow to be of practical interest.The class of primal-dual path-following interior point methods is considered the most successful.
Mehrotra's predictor-corrector algorithm provides the basis for most implementations of this class of methods.References
* Karmarkar, Narendra (1984). "A New Polynomial Time Algorithm for Linear Programming", "Combinatorica", Vol 4, no. 4, pp. 373–395.
* Mehrotra, Sanjay (1992). "On the implementation of a primal-dual interior point method", "SIAM Journal on Optimization", Vol. 2, no. 4, pp. 575--601.
*cite book|title = Numerical Optimization | first=Jorge| last = Nocedal | coauthors= and Stephen Wright| year=1999 | publisher=Springer | location=New York, NY| id=ISBN 0-387-98793-2
*cite book|title = Primal-Dual Interior-Point Methods | first=Stephen| last = Wright | year=1997 | publisher=SIAM | location=Philadelphia, PA| id=ISBN 0-89871-382-X
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