[ImkoMarijnissen]

This PR streamlines the outputs of --help when using cargo, and the output of the options used by minizinc --help pumpkin (using a style similar to Chuffed):

1. Move the clap struct arguments into their own categories.
2. Add a value_name to the clap struct arguments so that it is clear what type they use.
3. Update the .msc flag descriptions to only use a single line and to include the defaults/types.
4. Add requirements in the parsing of the flags, so that it is clear which flags are dependent on one another.

MiniZinc Output Difference

Previous:

Extra solver flags (use with --fzn-flags)
  --proof-path
    The output path for the proof file.

When solving a DIMACS instance, a DRAT proof is logged. In case of a FlatZinc model, a DRCP
proof is logged.

In case of a DRCP proof, if the file extension ends with `.gz`, a gzipped proof will be
produced.
  --proof-type
    What type of proof to log.

If the `proof_path` option is not provided, this is ignored.
  --learning-max-num-high-lbd-nogoods
    The number of high-lbd learned nogoods that are kept in the database.

Learned nogoods are kept based on the tiered system introduced in "Improving
SAT Solvers by Exploiting Empirical Characteristics of CDCL - Chanseok Oh (2016)".

Possible values: usize
  --learning-max-num-mid-lbd-nogoods
    The number of mid-lbd learned nogoods that are kept in the database.

This is based on the variation of the three-tiered system proposed in
"Improving Implementation of SAT Competitions 2017–2019 Winners".

Possible values: usize
  --learning-max-num-low-lbd-nogoods
    The number of low-lbd learned nogoods that are kept in the database.

This is based on the variation of the three-tiered system proposed in
"Improving Implementation of SAT Competitions 2017–2019 Winners".

Possible values: usize

Newly adjusted:

Extra solver flags (use with --fzn-flags)
  --proof-path
    The output path for the proof file. [possible values: string]
  --proof-type
    What type of proof to log. [default: scaffold] [possible values: scaffold, full]
  --learning-max-num-high-lbd-nogoods
    The number of high-lbd learned nogoods that are kept in the database. [default: 20000] [possible values: int]
  --learning-max-num-mid-lbd-nogoods
    The number of mid-lbd learned nogoods that are kept in the database. [default: 7000] [possible values: int]
  --learning-max-num-low-lbd-nogoods
    The number of low-lbd learned nogoods that are kept in the database. [default: 100000] [possible values: int]
  --learning-low-lbd-threshold
    The treshold determining whether a learned nogood is "low" LBD. [default: 3] [possible values: int]