# Optimization

Solves the optimization problem of continuous/discrete variables, given a model function $$f(x)$$ given the form:

\begin{split}\begin{align} &\underset{x}{\operatorname{maximize}}& & f(x) \\ &\operatorname{subject\;to} & &g_i(x) \leq 0, \quad i = 1,\dots,m \end{align}\end{split}

Where:

• $$f: \mathbb{R}^n \rightarrow \mathbb{R}$$: is the objective function to be maximized over the $$n$$-variable vector $$x$$

• $$g_i(x) \leq 0$$: are a set of inequality contraints to be satisfied.

## Usage

e["Problem"]["Type"] = "Optimization"

## Compatible Solvers

This problem can be solved using the following modules:

## Variable-Specific Settings

These are settings required by this module that are added to each of the experiment’s variables when this module is selected.

Name
• Usage: e[“Variables”][index][“Name”] = string

• Description: Defines the name of the variable.

## Configuration

These are settings required by this module.

Num Objectives
• Usage: e[“Problem”][“Num Objectives”] = unsigned integer

• Description: Number of return values to expect from objective function.

Objective Function
• Usage: e[“Problem”][“Objective Function”] = Computational Model

• Description: Stores the function to evaluate.

Constraints
• Usage: e[“Problem”][“Constraints”] = List of Computational Model

• Description: Stores constraints to the objective function.

## Default Configuration

These following configuration will be assigned by default. Any settings defined by the user will override the given settings specified in these defaults.

{
"Constraints": [],
"Has Discrete Variables": false,
"Num Objectives": 1
}


## Variable Defaults

These following configuration will be assigned to each of the experiment variables by default. Any settings defined by the user will override the given settings specified in these defaults.

{    }