文件名称：Local optimization of dynamic programs
文件大小：669KB
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更新时间：2022-03-11 11:37:45
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AnalgorithmisproposedforlocatingafeasiblepointsatisfyingtheKKTconditionstoaspecifiedtolerance of feasible inequality-path-constrained dynamic programs (PCDP) within a finite number of iterations. ThealgorithmisbasedoniterativelyapproximatingthePCDPbyrestrictingtheright-handsideofthepath constraints and enforcing the path constraints at finitely many time points. The main contribution of this article is an adaptation of the semi-infinite program (SIP) algorithm proposed in Mitsos (2011) to PCDP. It is proved that the algorithm terminates finitely with a guaranteed feasible point which satisfies the first-order KKT conditions of the PCDP to a specified tolerance. The main assumptions are: (i) availability of a nonlinear program (NLP) local solver that generates a KKT point of the constructed approximation to PCDP at each iteration if this problem is indeed feasible; (ii) existence of a Slater point of the PCDP that also satisfies the first-order KKT conditions of the PCDP to a specified tolerance; (iii) all KKT multipliers are nonnegative and uniformly bounded with respect to all iterations. The performance of the algorithm is analyzed through two numerical case studies.