:mod:`multiobjective` --- Multiobjective Test Problems
======================================================

.. automodule:: optproblems.multiobjective
    :members:

Example
-------

This example shows how to define a multiobjective problem by either returning
several objective values from one function, or supplying a list of objective
functions.

.. code:: python

    import random
    from optproblems import *

    # possible objective functions
    def function1(phenome):
        return sum(x ** 2 for x in phenome)

    def function2(phenome):
        return min(phenome), max(phenome)

    # either a single function or a list of objective functions
    # may be supplied as argument to Problem
    # they may return a scalar or a sequence of objective values

    # if the number of returned values of any function is > 1,
    # `num_objectives` must be given explicitly
    problem = Problem(function2, num_objectives=2)
    # generate random solutions
    solutions = [Individual([random.random() * 5 for _ in range(5)]) for _ in range(10)]
    # evaluate solutions
    problem.batch_evaluate(solutions)
    # objective values were stored together with decision variables
    for solution in solutions:
        print(solution.phenome, solution.objective_values)

    problem = Problem([function1, function2], num_objectives=3)
    # generate random solutions
    solutions = [Individual([random.random() * 5 for _ in range(5)]) for _ in range(10)]
    # evaluate solutions
    problem.batch_evaluate(solutions)
    # objective values were stored together with decision variables
    for solution in solutions:
        print(solution.phenome, solution.objective_values)