Model on Oil Platform Using Brain Storm Optimization Algorithm

Abstract

Logistics is a complex field, requires use bioinspired algorithms used to refer a solution of computational problems, based on the planning and implementation on existing models in the evolutionary process. However, other paradigms that can be taken in the creation of evolutionary algorithms also exist such as the forces of nature, which have been many algorithms based on water, gas and wind reactions. Many of the environments involving unstructured problems in this case a problem of accommodation vessels relate with survive supplies to an oil platform with limited resources, which can be considered from the perspective of brainstorm process. This process offer a wide range categorized models that ignore the possible solutions to the problem common situation in real life. The purpose of this research is to apply evolutionary computation properties of brain process to a problem related with technology, to corroborate through data mining analysis of how is the support of various companies which use technology and carry different types of goods deemed survival supplies. A model arrangement of supplies vessels was developed in order to enable learning of this intelligent logistics problem, modelling a problem from PEMEX (Oil Government Company in Mexico) using to resolve Brain Storm Optimization Algorithm.