Mathematics vs. COVID-19
Universidad Internacional Menéndez Pelayo (UIMP)
Mathematics plays an important role in mitigating the current situation of the Covid-19 crisis. In particular, I would like to emphasize the role of the area of Applied Mathematics known as Analytics. Analytics, also known as Operations Research, is a discipline that applies advanced analytical methods, based on Data, Mathematical Models and Algorithms, to help make better decisions and make better use of resources. Analytics methodologies have been applied with great success in different sectors and industries, and in this case, they can also help in the current health situation by proposing efficient and realistic solutions, and designing plans and future actions.
Las Matemáticas juegan un papel importante en mitigar la situación actual de la crisis Covid-19. En particular, me gustaría hacer énfasis en el papel del área de las Matemáticas Aplicadas conocida por Analytics. La Analytics, también conocida por Investigación Operativa, es una disciplina que aplica métodos analíticos avanzados, basados en Datos, Modelos Matemáticos y Algoritmos, para ayudar a tomar mejores decisiones y hacer un mejor uso de los recursos. Las metodologías de Analytics han sido aplicadas con mucho éxito en diferentes sectores e industrias, y en este caso, estas también pueden ayudar en la situación sanitaria actual proponiendo soluciones eficientes y realistas, y diseñando planos y actuaciones futuras.
Helena Ramalhinho gave an invited talk on “Business Applications of the Iterated Local Search” in the II Escuela de Invierno de la Red HEUR, Campus de Móstoles de la Universidad Rey Juan Carlos, November 6-8, 2019.
Marcelus Fabri and Helena Ramalhinho attend the INFORMS 2019 Annual Meeting (INFORMS 2019), October 20-23, 2019, Seattle, Washington, USA, and presented a talk on “A Simulation-based Iterated Local Search for The In-house Logistics Routing Problem” .
Abstract: The objective of this work is to optimize the internal logistics processes in the car assembling company SEAT S.A., a Volkswagen subsidiary. We focus on the In-house Logistics Routing Problem (ILRP), an extension of the VRP. In the ILRP the routes are fixed and cannot be modified; the demand is unknown; the fleet is homogeneous; there are time-window and back-orders constraints. To solve the ILRP, we propose an Integer Linear Programming (ILP) model and a Simulation Iterated Local Search (SimILS) algorithm. We conducted experiments based on real company’s data. Results showed that the SimILS provided the best overall results overcoming both the ILP approach and the current company’s solution.
Marcelus Fabri and Helena Ramalhinho attend the Metaheuristics Internacional Conference 2019 in Cartagena de la Indias, Colombia in July 2019. They present a joint work with title “Internal logistics routing optimization”.
The work is about the internal logistics in a car manufacture company. The Internal Logistics is an important activity that can lead to improve the efficiency of the production and cost reduction. In this work we describe an internal logistics routing problem in important automotive company and propose an Iterated Local Search algorithm to solve this problem in a realistic environment. This algorithm will be incorporated by the company change the actual static system to a more dynamic and automatic one. We study also the impact of this new system in the company enable the managers to make better decisions and make easier the implementation.