A constant-potential infeasible-start interior-point algorithm with computational experiments and applications

A constant-potential infeasible-start interior-point algorithm with computational experiments and applications

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Article ID: iaor20011026
Country: United States
Volume: 9
Issue: 2
Start Page Number: 107
End Page Number: 152
Publication Date: Feb 1998
Journal: Computational Optimization and Applications
Authors: ,
Keywords: programming: probabilistic
Abstract:

We present a constant-potential infeasible-start interior-point (INFCP) algorithm for linear programming problems with a worst-case iteration complexity analysis as well as some computational results. The performance of the INFCP algorithm is compared to those of practical interior-point algorithms. New features of the algorithm include a heuristic method for computing a ‘good’ starting point and a procedure for solving the augmented system arising from stochastic programming with simple recourse. We also present an application to large scale planning problems under uncertainty.

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