Maintaining ``semi-feasibility'' of each iterate. 

Efficiently handling problems with many ``sequentially related'' objectives and/or constraints.

Availability of both Fortran (FFSQP) and C (CFSQP) source code, thus both can be easily integrated into user's own program.

Ability to search for an initial feasible point satisfying all linear constraints and nonlinear inequality constraints.

Ability to generate iterates satisfying all linear constraints and nonlinear inequality constraints (mandatory for many applications), starting from a feasible point.

Ability to improve objective function after each iteration or after at most four iterations (user's option) if there is no nonlinear equality constraints.

Ability to handle multiple competing objective functions (minmax problems).

Finite difference approximation to gradients if exact gradients are not provided by the user.

Global convergence and fast (two-step superlinear) local convergence.

Special scheme in CFSQP to efficiently handle problems with many more objectives or/and constraints than variables (finely discretized semi-infinite problems).

Interface in FFSQP to use an automatic differentiation program ADIFOR (the interface is not supported at this time).

Interface available for AMPL, NIMBUS, Diffpack, Scilab, LPL, and Matlab (the interface is not supported at this time).

Availability of original authors to discuss any theoretical and practical issues related to FSQP.