Container for optimization results for multi objective problems.

Attributes¶

success: bool

Optimization success

vars_int: np.array

Pareto-optimal variables, shape: (n_pop, n_vars_int)

vars_float: np.array

Pareto-optimal variables, shape: (n_pop, n_vars_float)

objs: np.array

Pareto front objective function values, shape: (n_pop, n_objectives)

cons: np.array

Parteo front Constraint values, shape: (n_pop, n_constraints)

problem_results: Object

The results of the variable application to the problem

pname: str

The problem’s name

vnames_int: list of str

The int variable names

vnames_float: list of str

The float variable names

onames: list of str

The names of objectives

cnames: list of str

The names of constraints

Public members¶

MultiObjOptResults(problem, success, vars_int, vars_float, ...)[source]

Constructor

__str__()[source]

Return str(self).

plot_pareto(obj_0=0, obj_1=1, ax=None, figsize=(5, 5), s=50, ...)[source]

Get figure that shows the pareto front

find_pareto_objmix(obj_weights, max=False)[source]

Find the point on the pareto front that approximates best the given weights of objectives