Minimize absolute value

class rtctools.optimization.min_abs_goal_programming_mixin.MinAbsGoalProgrammingMixin(*args, **kwargs)

Bases: rtctools.optimization.goal_programming_mixin_base._GoalProgrammingMixinBase

Similar behavior to GoalProgrammingMixin, but any MinAbsGoal passed to min_abs_goals() or min_abs_path_goals() will be automatically converted to:

1. An auxiliary minimization variable
2. Two additional linear constraints relating the auxiliary variable to the goal function
3. A new goal (of a different type) minimizing the auxiliary variable

min_abs_goals() → List[rtctools.optimization.min_abs_goal_programming_mixin.MinAbsGoal]

User problem returns list of MinAbsGoal objects.

Returns:A list of goals.

min_abs_path_goals() → List[rtctools.optimization.min_abs_goal_programming_mixin.MinAbsGoal]

User problem returns list of MinAbsGoal objects.

Returns:A list of goals.

class rtctools.optimization.min_abs_goal_programming_mixin.MinAbsGoal

Bases: rtctools.optimization.goal_programming_mixin_base.Goal

Absolute minimization goal class which can be used to minimize the absolute value of the goal’s (linear) goal function. Contrary to its super class, the default order is 1 as absolute minimization is typically desired for fully linear problems.

class rtctools.optimization.min_abs_goal_programming_mixin.MinAbsStateGoal(optimization_problem)

Bases: rtctools.optimization.goal_programming_mixin_base.StateGoal, rtctools.optimization.min_abs_goal_programming_mixin.MinAbsGoal

__init__(optimization_problem)

Initialize the state goal object.

Parameters:optimization_problem – OptimizationProblem instance.