Simplicial Decomposition for Convex Generalized Networks

Abstract The simplicial decomposition algorithm is specialized to solve nonlinear programs with generalized network constraints. Large scale problems can be solved efficiently by capitalizing on the intrinsic structure of the generalized network basis in the subproblem steps. The performace of the master problem is improved using a forcing sequence strategy to solve the master inexactly in a controlled fashion. The resulting software system (GNSD) is capable of solving large problems from a wide variety of applications. We investigate tactics that affect its performance and compare GNSD with other nonlinear programming codes.

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