Feasible Sequential Quadratic Programming for Finely Discretized Problems from Sip
نویسنده
چکیده
A Sequential Quadratic Programming algorithm designed to eeciently solve nonlinear optimization problems with many inequality constraints, e.g. problems arising from nely discretized Semi-Innnite Programming, is described and analyzed. The key features of the algorithm are (i) that only a few of the constraints are used in the QP sub-problems at each iteration, and (ii) that every iterate satisses all constraints.
منابع مشابه
An SQP Algorithm for Finely Discretized Continuous Minimax Problems and Other Minimax Problems with Many Objective Functions
A common strategy for achieving global convergence in the solution of semi-innnite programming (SIP) problems, and in particular of continuous minimax problems, is to (approximately) solve a sequence of discretized problems, with a progressively ner discretization meshes. Finely discretized minimax and SIP problems, as well as other problems with many more objec-tives/constraints than variables...
متن کاملAn Algorithm for a Nonlinear Optimization Problem Using Replicator Equations
This paper proposes an algorithm for a nonlinear optimization problem utilizing replicator equations. The problem is to Þnd the global minimum of a multivariate function in which each variable has a bounded feasible region. First, the feasible region of each variable is discretized and expressed as a set of nodes, and the feasible region of the problem is expressed as a set of combinations of t...
متن کاملA TRUST-REGION SEQUENTIAL QUADRATIC PROGRAMMING WITH NEW SIMPLE FILTER AS AN EFFICIENT AND ROBUST FIRST-ORDER RELIABILITY METHOD
The real-world applications addressing the nonlinear functions of multiple variables could be implicitly assessed through structural reliability analysis. This study establishes an efficient algorithm for resolving highly nonlinear structural reliability problems. To this end, first a numerical nonlinear optimization algorithm with a new simple filter is defined to locate and estimate the most ...
متن کاملA Feasible Trust-Region Sequential Quadratic Programming Algorithm
An algorithm for smooth nonlinear constrained optimization problems is described, in which a sequence of feasible iterates is generated by solving a trust-region sequential quadratic programming (SQP) subproblem at each iteration, and perturbing the resulting step to retain feasibility of each iterate. By retaining feasibility, the algorithm avoids several complications of other trust-region SQ...
متن کاملSemi–Monotonic Augmented Lagrangians for Optimal Control and Parameter Identification
Optimization and inverse problems governed with partial differential equations are often formulated as constrained nonlinear programming problems via the Lagrange formalism. The nonlinearity is treated using the sequential quadratic programming. A numerical solution then hinges on an efficient iterative method for the resulting saddle–point systems. In this paper we apply a semi–monotonic augme...
متن کامل