Abstract
This paper introduces sequential convex programming (SCP), a local optimzation method for solving nonconvex optimization problems. A full-step SCP algorithm is presented. Under mild conditions the local convergence of the algorithm is proved as a main result of this paper. An application to optimal control illustrates the performance of the proposed algorithm. © 2010 Springer -Verlag Berlin Heidelberg.
Cite
CITATION STYLE
Dinh, Q. T., & Diehl, M. (2010). Local convergence of sequential convex programming for nonconvex optimization. In Recent Advances in Optimization and its Applications in Engineering (pp. 93–102). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-12598-0_9
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