Many geodetic applications require the minimization of a convex objective function subject to some linear equality and/or inequality constraints. If a system is singular (e.g., a geodetic network without a defined datum) this results in a manifold of solutions. Most state-of-the-art algorithms for inequality constrained optimization (e.g., the Active-Set-Method or primal-dual Interior-Point-Methods) are either not able to deal with a rank-deficient objective function or yield only one of an infinite number of particular solutions.
Roese-Koerner, L., Schuh, W. Convex optimization under inequality constraints in rank-deficient systems,
Springer Berlin Heidelberg, 2014, с.415-426.
Roese-Koerner, L., Schuh, W. .
Convex optimization under inequality constraints in rank-deficient systems.
: Springer Berlin Heidelberg, 2014, с.415-426.
Roese-Koerner, L., Schuh, W. (2014)
Convex optimization under inequality constraints in rank-deficient systems,
: Springer Berlin Heidelberg, с.415-426
Roese-Koerner, L., & Schuh, W.
(2014).
Convex optimization under inequality constraints in rank-deficient systems. Journal of Geodesy. Springer Berlin Heidelberg, 88 (5), с.415-426.
