New infeasible interior-point algorithm based on monomial method

We propose a new infeasible path-following algorithm for the convex linearly-constrained quadratic programming problem. This algorithm utilizes the monomial method rather than Newton's method for solving the KKT equations at each iteration. As a result, the sequence of iterates generated by thi...

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Vydáno v:Computers & operations research Ročník 23; číslo 7; s. 653 - 666
Hlavní autoři: Yi-Chih, Hsieh, Bricker, Dennis L.
Médium: Journal Article
Jazyk:angličtina
Vydáno: Oxford Elsevier Ltd 01.07.1996
Elsevier Science
Pergamon Press Inc
Témata:
Algorithms
Applied sciences
Computer programming
Exact sciences and technology
Mathematical programming
Operational research and scientific management
Operational research. Management science
Operations research
Studies
Performance evaluation
Path following method
Interior point method
Quadratic programming
Algorithm
Convex programming
Constrained optimization
Knapsack problem
Mathematical programming
ISSN:0305-0548, 1873-765X, 0305-0548
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Shrnutí:We propose a new infeasible path-following algorithm for the convex linearly-constrained quadratic programming problem. This algorithm utilizes the monomial method rather than Newton's method for solving the KKT equations at each iteration. As a result, the sequence of iterates generated by this new algorithm is infeasible in the primal and dual linear constraints, but, unlike the sequence of iterates generated by other path-following algorithms, does satisfy the complementarity equations. Performance of this new algorithm is demonstrated by the results of solving QP problems (both separable and nonseparable) which are constructed so as to have known optimal solutions. Additionally, results of solving continuous quadratic knapsack problems indicate that for problems of a given size, the computational time of this new algorithm is less variable than other algorithms.
Bibliografie:ObjectType-Article-1
SourceType-Scholarly Journals-1
content type line 14
ISSN:0305-0548
1873-765X
0305-0548
DOI:10.1016/0305-0548(95)00068-2