Brief: Rewrite and optimize QuadProg++ on top of Eigen, extend rational_quadprog fitter with a LS quadratic objective, and improve inequality scheduling.
Details:
 - Rewitre and optimize QuadProg++ to be fully based on Eigen. This leads to a more readable code, and significant speed up to compute step directons and add/delete constraints.
 - Generalize QuadProg++ API to allow passing the inital guess, to export the resulting active-set, to pass a list of inequalities to satisfy first, and options and schedule the inequalities.
 - Add various inequality scheduling heuristics:
   - WorstFirst : the default for QuadProg++
   - SlidingWindows: treat the worst of the current subset, and shift/grow the subset (the default for rational_quadprog)
   - WorstSetFirst: treat all the N worst before checking for the others
 - Add new options for rational_quadprog:
    _scheduling_mode = args.get_string("scheduling-mode","SlidingWindows"); -> can also be "WorstFirt" or "WorstSetFirst"
    _scheduling_chunk_size = args.get_int("scheduling-chunk-size",-1); -> the default is usually very good
    _scheduling_grow_factor = args.get_float("scheduling-grow-factor",-1); -> not recommended
    _export_qp = args.is_defined("export-qp"); -> export QP problem to files for testing with other solvers
    _delta = args.get_float("delta", 1);
    _add_ls_energy = args.is_defined("add-ls-energy"); -> recommended
 - Update rational_quadprog_parallel to reflect API changes