A Constant-Potential Infeasible-Start Interior-Point Algorithmwith Computational Experiments and Applications

Authors:
Abbas Seifi;Levent Tunçel
Affiliations:
Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, Ontario, Canada, N2L 3G1. E-mail: aseifi@dantzig.uwaterloo.ca;Department of Combinatorics and Optimization, Faculty of Mathematics, University of Waterloo, Waterloo, Ontario, Canada, N2L 3G1. E-mail: ltuncel@math.uwaterloo.ca
Venue:
Computational Optimization and Applications
Year:
1998

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Abstract

We present a constant-potential infeasible-start interior-point(INFCP) algorithm for linear programming (LP) problems witha worst-case iteration complexity analysis as well as somecomputational 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 procedurefor solving the augmented system arising from stochastic programming withsimple recourse. We also present an applicationto large scale planning problems under uncertainty.