|FSQP||Authors||Dr. Eliane R. Panier, University of Maryland
Prof. Andre Tits
|Algorithm||SQP (Sequential Quadratic Programming) type algorithm modified so as to generate feasible iterates. The basic problem solved is (where the variable x is n-dimensional)
Two phase operation :
Phase I - generate iterate satisfying all linear constraints and nonlinear inequality constraints.
Phase II - minimize maximum of objectives. Iterates satisfy all constraints except nonlinear equality constraints (which are asymptotically satisfied).
|Modeling Languages link||AMPL, NIMBUS, LPL, Matlab|
|Commercial Status||FSQP Distribution|
|Remarks||Portable implementations (in both C and Fortran) of the Feasible Sequential Quadratic Programming (FSQP) algorithm, a superlinearly convergent algorithm for directly tackling optimization problems with:
Multiple competing linear/nonlinear objective functions (minimax).
linear/nonlinear inequality constraints.
linear/nonlinear equality constraints.
The algorithm contains special provisions for
Maintaining "semi-feasibility" of each iterate.
Efficiently handling problems with many "sequentially related" objectives and/or constraints.
|References||C. T. Lawrence, J. L. Zhou and A. L. Tits, User's Guide for CFSQP Version 2.5: A C Code for Solving (Large Scale) Constrained Nonlinear (Minimax) Optimization Problems, Generating Iterates Satisfying All Inequality Constraints, Institute for Systems Research, University of Maryland, Technical Report TR-94-16r1, College Park, MD 20742, 1997.
J. L. Zhou, A. L. Tits and C. T. Lawrence, User's Guide for FFSQP Version 3.7 : A Fortran Code for Solving Optimization Programs, Possibly Minimax, with General Inequality Constraints and Linear Equality Constraints, Generating Feasible Iterates, Institute for Systems Research, University of Maryland,Technical Report SRC-TR-92-107r5, College Park, MD 20742, 1997.