Unary Constraint

Overview

A Unary Constraint in Verteego applies a single static bound to one variable, imposing a specific limitation on its value. This type of constraint is essential for ensuring that the variable remains within acceptable limits, thereby maintaining the integrity and feasibility of the optimization model.

Application

Unary Constraints are used to enforce a lower or upper limit on a variable, which can be crucial for maintaining business rules and operational limits. For example, setting a minimum price to ensure profitability.

Parameters

• column: Specifies the name of the column that contains the variable to be constrained. This variable represents an element of the data that is crucial for the optimization process.

• bound: A numeric value that will serve as the boundary for the variable. This number can act as either a cap (upper limit) or a floor (lower limit) depending on the operator used.

• operator: Defines the type of constraint relation between the variable and the bound. Options include:

  • equal – The variable must be exactly equal to the bound.

  • lesser – The variable must be less than or equal to the bound.

  • greater – The variable must be greater than or equal to the bound.

Example

Here is an example of how to configure a Unary Constraint in YAML format to ensure that a price cannot fall below zero:

  lower_bound_on_price:
    constraint_type: unary
    column: price
    operator: greater
    bound: 0

Best Practices

When implementing Unary Constraints, it is crucial to:

• Clearly identify the variable that needs bounding to avoid unintended constraints on other elements of the dataset.

• Select appropriate bounds that align with operational and business goals.

• Use the correct operator to accurately reflect the intended limitation, whether it's ensuring a minimum value, capping a maximum value, or setting an exact requirement.