MP-Opt-Model 2.0

What's New in MP-Opt-Model 2.0

Released July 8, 2020

Below is a summary of the changes since version 1.0 of MP-Opt-Model. See
the CHANGES.md file for all the gory details. For release notes
for previous versions, see Appendix C of the MP-Opt-Model User's
Manual.

New Features

• Add new 'fsolve' tag to have_fcn() to check for availability of
  fsolve() function.
• Add nleqs_master() function as unified interface for solving
  nonlinear equations, including implementations for fsolve and
  Newton's method in functions nleqs_fsolve() and nleqs_newton(),
  respectively.
• Add support for nonlinear equations (NLEQ) to opt_model. For
  problems with only nonlinear equality constraints and no costs,
  the problem_type() method returns 'NLEQ' and the solve()
  method calls nleqs_master() to solve the problem.
• New functions:
  • mpopt2nleqopt() creates or modifies an options struct for
    nleqs_master() from a MATPOWER options struct.
  • nleqs_fsolve() provides implementation of unified nonlinear
    equation solver interface for fsolve.
  • nleqs_master() provides a single wrapper function for calling
    any of MP-Opt-Model's nonlinear equation solvers.
  • nleqs_newton() provides implementation of Newton's method solver
    with a unified nonlinear equation solver interface.
  • opt_model/params_nln_constraint() method returns parameters for
    a named (and optionally indexed) set of nonlinear constraints.
  • opt_model/params_nln_cost() method returns parameters for a
    named (and optionally indexed) set of general nonlinear costs.

Other Changes

• Add to eval_nln_constraint() method the ability to compute constraints
  for a single named set.
• Skip evaluation of gradient if eval_nln_constraint() is called with
  a single output argument.
• Remove redundant MIPS tests from test_mp_opt_model.m.
• Add tests for solving LP/QP, MILP/MIQP, NLP and NLEQ problems via
  opt_model/solve().
• Add Table 6-1 of valid have_fcn() input tags to User's Manual.