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Fixed Cost Metric

A fixed cost metric in Optimize is one whose value is determined by a fixed cost associated with each of the unique levels in the optimization scenario that are involved in the solution. For example, suppose you are looking to choose which of many possible locations to place distribution centers and account for or even minimize your overall total costs. The cost of opening each individual distribution center often includes a fixed cost component (in addition to possible variable costs). Any pot...

Reviewing Detailed Optimization Scenario Results

There are two primary means to review the details of the results of an optimization scenario. First, to be clear, the "detailed results" refer to the optimal values that were determined for the Output Variable, for every row in the scenario's dataset (or, also stated as, for every unique value of the scenario's Dimension Variable). Method 1 Within Optimize, select the scenario from the scenario list, click the Selected Scenario drop down button, and then select Scenario Analysis -> Detai...

Implementation Job Settings

To edit the settings for an Optimize implementation job, first select the job from the Implementation Jobs list and click Edit Settings. (To first create an Implementation Job and to learn more about them, see https://support.lityxiq.com/873919-Optimize-Implementation-Jobs). (NOTE: Before you can edit the settings of an implementation job, you must first have at least one Result Catalog setup. See the article https://support.lityxiq.com/051043-Optimization-Result-Catalogs for more information o...

Compare Optimization Scenarios

It is often desired to compare the output of two or more scenarios in order to conduct what-if analysis. This can show, for example, the effect that a business constraint has on the final output metrics, or the tradeoffs being made between two different objective functions. To get started, after all the scenarios you wish to compare have finished to successful execution, select any of them in the list of scenarios within the correct Scenario Library. Then click Scenario Analysis -> Compare S...

Analyze an Optimization Scenario Result

After an optimization finishes a successful execution you will want to review the results. One method for doing that is simply called a Scenario Analysis Summary. It provides an exploratory method for drilling down in the the optimal results at various levels of aggregation (based on the attributes you defined in the scenario settings) and for any metrics (as defined in the scenario settings). If you want to compare the outputs of two scenarios, or multiple versions of the same scenario, see ht...

Executing and Scheduling an Optimization Scenario

Optimization scenarios can be executed immediately, or on a schedule, similar to other objects in LityxIQ. To execute a scenario, select the scenario library, and then select the scenario from the scenario list. Click Run Scenario -> Execute Now from the selected scenario menu or from the right click menu. If you are scheduling the scenario execution, see https://support.lityxiq.com/882325-Using-the-Scheduling-Dialog for a description for how to use the common scheduler dialog. If you ...

Scheduling or Automating an Implementation Job

Optimization Implementation jobs can be setup to run on an automatic schedule (such as every Saturday at 3:00 am) or to run automatically. An implementation job will run automatically when both the dataset related to the scenario AND the scenario itself have changed since the last run of the implementation job. To schedule an implementation job, first select the correct job from the list of all implementation jobs within Optimize, then click Run Job -> Schedule It from the Selected Job menu ...

Optimize Implementation Jobs

An Implementation Job in LityxIQ's Optimize allow you to store the detailed results of an optimization run into a separate dataset that can be used elsewhere in the platform. For example, if the optimization problem was to determine the optimal number of digital impressions to buy for each partner site, week, and creative, and you successfully ran an optimization scenario to give you a result, an implementation job will push the details of the optimized buy recommendations into a dataset. Addit...

Optimization Result Catalogs

An optimization result catalog is a special dataset where the results of implemented scenarios are stored. They are created initially by the user, as will be described here, and updated with new data by Implementation Jobs. The variables placed in an Optimization Result Catalog are one variable for each optimization dimension, and a variable representing the optimization result (e.g., a 1 or 0 if it was a binary optimization problem). One row is placed into the catalog for each row in the datase...

Create and Maintain Optimization Libraries

Optimization libraries are a way to organize your optimization scenarios, as well as to use permissions to ensure access to only those who should have it. This document describes how to create and maintain optimization libraries. To manage optimization libraries, first click the Libraries link within the Optimize area of LityxIQ. Create a New Optimization Library To create a new library, click the Create Library button. You will then enter the name for the new library, and optionally ...

Edit Constraint - Defining the Basis

The Basis for Constraint tab provides important options when defining a constraint. It determines the subset of the problem, also thought of as the subset of the data, to which the constraint will apply. Depending on the options used, it may lead to creating multiple, or even a large number of, constraints. For example, you may have a budget constraint that only applies to 3 of the 8 customer segments in the dataset. In that case, the budget upper bound you enter does not apply to the entire p...

Edit Constraint - Basic Setup

Editing a constraint in an optimization scenario involves a number of options that, taken together, will define how the constraint works. LityxIQ will take care of creating the mathematical code that describes the constraint before it executes the optimization scenario. The Edit Constraint dialog has three tabs. All of the options available in each tab will be described in more detail below and other documents, but in short, these tabs are: - Basic Setup - this tab is used to give it a...

Manage Optimization Constraints

Constraints in an optimization scenario are defined and managed in the Constraints tab. Constraints that have been created will appear in the list of constraints. This document explains how to create new constraints and manage existing ones in this tab. Add Constraint - This box allows you to select a type of constraint to add to the optimization scenario. The different types available are described here: https://support.lityxiq.com/524228-Types-of-Optimization-Constraints. Once you select...

Simple Optimization Metric

A simple metric in Optimize is one computed by applying a linear function to summarize rows in the dataset. The linear function is built up by multiplying one or both of 1) a chosen Data Element 2) the Optimization Output value for each row, and then summarizing over rows by one of four methods: SUM, AVG, MIN, MAX. By far the most common method is to SUM over the rows. Here is an example to help make it easier to understand. It is also helpful to try different options in LityxIQ and see the ...

Complex Optimization Metric

A complex metric in Optimize is one that is based on other metrics (simple and/or complex). A complex metric is built up in three components: Numerator (N), Denominator (D), and Right Hand Side (RHS). The RHS component itself can be either another metric or a constant value, and can be connected to N/D with one of the four arithmetic signs. Effectively therefore, a complex metric can take forms such as: - N/D = straight ratio of two metrics - N (plus/minus/times/divided by) RHS metric = sum (o...

Define Optimization Metrics

Optimization problems require one or more metrics to be defined. The metrics are used as a basis for optimization, or for helping define the constraints of the problem. In either case, defining an optimization metric in LityxIQ follows the same process. The Defined Metrics area of the Metrics & Objective tab within the Scenario Settings dialog looks like the following: For metrics that you have defined, the icons can be used to Edit and Delete the metrics, respectively. To create a new metric...

Edit a Scenario Definition

After creating an optimization scenario, the next step is defining how it will work. This document provides information on the steps and details for defining a scenario. It is helpful to understand the basic concepts related to doing optimization in LityxIQ. See this document as a starting point: https://support.lityxiq.com/971326-Conceptual-Overview-of-LityxIQ-Optimize. First, select the scenario from the list of available scenarios in the selected scenario library. Then click Edit Settings f...

Create a New Optimization Scenario

To create a new optimization scenario, follow these steps: 1) Navigate to the Scenarios area within Optimize. 2) Select the Scenario Library in which you would like to place the new scenario, then click the Create new Scenario button: 3) Enter a name for the new scenario, as well as an optional description. You also have the option of placing the new scenario into a different library. Then click OK. This will open the Edit Scenario dialog for the new scenario. See https://support.lityx...

Optimize Overview

In LityxIQ, the Optimize area allows you to optimize complex business decisions while accounting for business constraints. To access this functionality, select Optimize in the left panel of LityxIQ. Optimize has four main areas, which are explained below. Scenarios - Scenarios are the method of defining Optimization runs in LityxIQ. They provide a way of modifying data, rules, constraints, and outputs so that you can compare one result to another (i.e., business scenarios) as a way of determ...