Bregman Proximal Relaxation of Large-Scale 0–1 Problems

Authors:
Krzysztof C. Kiwiel;P. O. Lindberg;Andreas Nõu
Affiliations:
Systems Research Institute, Newelska 6, 01-447 Warsaw, Poland. kiwiel@ibspan.waw.pl;Linköping University, SE-58183 Linköping, Sweden. polin@math.liu.se;Royal Institute of Technology, SE-100 44 Stockholm, Sweden. andreasn@math.kth.se
Venue:
Computational Optimization and Applications
Year:
2000

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Abstract

We apply a recent extension of the Bregman proximal method for convexprogramming to LP relaxations of 0–1 problems. We allow inexactsubproblem solutions obtained via dual ascent, increasing their accuracysuccessively to retain global convergence. Our framework is appliedto relaxations of large-scale set covering problems that arise inairline crew scheduling. Approximate relaxed solutions are used toconstruct primal feasible solutions via a randomized heuristic.Encouraging preliminary experience is reported.