Otimização de um sistema de distribuição de bebidas

Abstract

Given the growing need of the production market to simultaneously reach an increasing number of scope and scale in the distribution of its products to a society, the optimization of processes comes whenever creating alternatives so that there is a greater reduction in the costs of the operation. and increased process efficiency. In this sense, the logistical process has never been more strategic for the industrial sector. After the 1980s, logistics began to have a revolutionary development, driven by the demands caused by the Industrial Revolution, by the change in the world economy and by the great growth in demand, in which all the supply chain management that plans, implements and controls the efficient and economical flow and storage of raw materials, semi-finished materials and finished products are controlled by the area. In this context, engineering presents itself as a fundamental piece for the application of process optimization involving the development of computational computational algorithms that bring an optimal solution to the problem. One of the methods used for data clustering involving the distribution of products in engineering is the K-Means Method, a model that aims to partition n dissipation of groups, presenting each observation belonging to the group closest to the average, which results in the division of the data on a Voronoi diagram. Thus, the objective of this work consists in the computational optimization of the beverage distribution system of the Direct Distribution Center of a Brewery, using NP-Difficult resolution algorithms (computationally difficult problem) through the Python programming language, in order to understand the best scenario of grouping customers and delivery routes to minimize the daily distance traveled during the company's beverage distribution.