Make solver interface more unified

Fixes #99

 - Model.optimize no longer gives parameter values by default. The
   defaults are left to the solvers.
 - Each solver has a _SUPPORTS_MILP attribute which can be used to
   determine if it solves mixed integer programs.
 - get_solver_name will raise a SolverNotFound exception when it can not
   find a suitable solver.
 - Each solver has a solver_name attribute which is used instead of
   attempting to remove the word "solver".
 - Solver options are now more unified. All solvers now accept (in
   addition to their own additional ones)
   - time_limit
   - tolerance_feasibility
   - tolerance_markowitz
   - iteration_limit
Remove deprecated solver functions
solvers no longer uses external parameters

Instead of importing parameters from an external parameters module, each
solver defines its own parameters. The following solvers were updated:
 - glpk
 - gurobi
 - cplex
Additionally, the parameter handling code was simplified,
making it more readable and easier to debug.
glpk_solver parameter improvements

The following changes were made:
 - raise an exception when passed an unsupported option.
 - Use tolerance_feasibility instead of tolerance_optimality for tol_dj
   and tol_bnd
 - support for lp_method as strings
cglpk supports lp_method and verbose options

also warns for unsupported threads and mip_gap_abs
improve cplex parameter handling

When setting parameters, the cplex solver will now convert strings
encoding the cplex constant to the constant itself. For example, setting
lp_method="auto" will cause execution of
lp.parameters.lpmethod.set(lp.parameters.lpmethod.auto)

Additionally, an invalid paramter will raise a ValueError. Finally,
verbose is handled as an option to allow output (silenced by default).
gurobi parameters updated

Now supports lp_method strings and verbose.