**4. Optimization methods**

Many different practical optimization methods have been used in critical industries. Generally, the aim of optimization is to increase productivity, energy and cost

**5**

**Author details**

Artificial Intelligence Center, Vale, Brisbane, Australia

© 2019 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium,

\*Address all correspondence to: ali@soofastaei.net

provided the original work is properly cited.

Ali Soofastaei

*Introductory Chapter: Advanced Analytics and Artificial Intelligence Applications*

efficiency, and safety. Prior to the data revolution, traditional optimization models were used for practical business solutions. Currently, the quantity and quality of collected data in many industries have created an opportunity to use innovative optimization solutions to achieve better outcomes. Of all the current optimization approaches, genetic algorithm, particle swarm, ant colony, bee colony, firefly algorithm (FA), and tabu search are the most prevalent in critical industries.

The aforementioned AA, BDA, and AI applications for prediction, optimization, and decision-making may help industries increase efficiency across various dimensions as well as take action to solve global environmental and energy consumption problems. The case studies presented in the following chapters illustrate the possibilities for using AA, BDA, and AI to solve business problems across

*DOI: http://dx.doi.org/10.5772/intechopen.89784*

different industries.

#### *Introductory Chapter: Advanced Analytics and Artificial Intelligence Applications DOI: http://dx.doi.org/10.5772/intechopen.89784*

efficiency, and safety. Prior to the data revolution, traditional optimization models were used for practical business solutions. Currently, the quantity and quality of collected data in many industries have created an opportunity to use innovative optimization solutions to achieve better outcomes. Of all the current optimization approaches, genetic algorithm, particle swarm, ant colony, bee colony, firefly algorithm (FA), and tabu search are the most prevalent in critical industries.

The aforementioned AA, BDA, and AI applications for prediction, optimization, and decision-making may help industries increase efficiency across various dimensions as well as take action to solve global environmental and energy consumption problems. The case studies presented in the following chapters illustrate the possibilities for using AA, BDA, and AI to solve business problems across different industries.
