Estudio de factibilidad para la aplicación de algoritmos de estimación de distribución al problema de secuenciación de vehículos

The main objective of an automobile production plant is to deliver on time and form the orders that are received daily. These orders are not homogeneous since they involve large quantities of cars that generally belong to different models and must be painted in different colors. The car sequencing problem that takes these characteristics into account was proposed by the Renault Company in 2005 as part of the ROADEF Challenge. This problem is NP-Hard and various techniques have been proposed to solve it, from exact methods to different heuristic algorithms. This work presents a feasibility study to apply two Distribution Estimation Algorithms (EDAs) to solve this problem. In addition, three important aspects are presented: the adaptation process of the algorithms, a technique for the execution of the algorithms called the "Stepped Approach with Discard" and a methodology that involves tolerance in the substitution of the individuals. The results obtained by the algorithms are also shown. The analysis of the results shows the algorithms adaptation process and the adjustments that can be made to improve their competence with the state of art.