# Decision Optimization

## What is Decision Optimization?

Decision Optimization is a mathematical process that helps businesses make the best possible decisions by optimizing input parameters and business rules. This process takes data and models as inputs, applies mathematical algorithms to analyze the data, and generates output that helps businesses make better decisions.

## How Does Decision Optimization Work?

DO works by using mathematical models that take into account various variables, constraints, and objective functions that are inherent in the decision-making process. For example, a company might want to minimize costs while maximizing profits, or a transportation company might want to minimize shipping times while minimizing costs. These complex problems can be modeled, optimized, and solved using DO algorithms.

DO involves several steps:

• Identify the problem to be solved

• Define the decision variables, constraints, and objective function

• Develop a mathematical model that represents the problem

• Optimize the model using a DO algorithm

• Evaluate the results, select the best solution, and implement it

## Why Decision Optimization is Important?

Decision Optimization is important because it helps businesses make better decisions by optimizing input parameters and business rules. This process can be applied to a wide range of business problems, including supply chain optimization, workforce planning, risk management, and energy management.

## The Most Important Decision Optimization Use Cases

Decision Optimization can be applied to a wide range of business problems, including:

• Supply chain optimization

• Workforce planning

• Risk management

• Energy management

• Scheduling

• Asset management

• Portfolio optimization

• Routing optimization

• Other Technologies or Terms Closely Related to Decision Optimization

Other technologies that are closely related to Decision Optimization include:

• Machine Learning

• Artificial Intelligence

• Operations Research

• Mathematical Optimization

• Convex Optimization

• Nonlinear Programming

• Prescriptive Analytics

## How H2O can Improve Decision Optimization

H2O provides a powerful platform for Decision Optimization that integrates with other machine learning and data engineering tools. H2O's machine learning algorithms can be used to build predictive models that can be optimized using Decision Optimization. H2O also provides a user-friendly interface for building and deploying Decision Optimization models, making it easy for users to get started with this powerful technology.

Decision Optimization is a powerful tool for businesses looking to make better decisions by optimizing input parameters and business rules. This process can be applied to a wide range of business problems, including supply chain optimization, workforce planning, risk management, and energy management. By using H2O, businesses can leverage the power of Decision Optimization to get insights into their data and make better decisions.