Google Scholar ResearchGate ORCID RESEARCHERID SCOPUS
Research Interests
Operations Research, Intelligent Optimization, Business Analytics, Logistics, Metaheuristics, Iterated Local Search, Combinatorial Optimization, Scheduling, Supply Chain Management
Business Analytics Research Group (BARG)
Business Analytics is the discipline of applying data-driven analytical methods and fact-based decision making to help making better decisions in business. Business Analytics focuses on developing new insights and understanding of business performance based on broad set of analytical methodologies from areas like Operations Research, Artificial Intelligence, Statistics, etc.
Actual Research Projects
- (2020-2023) Mobility Optimization for Social Care Services. Industrial PhD. Funding: Barcelona City Council (Institut Municipal Persones amb Discapacitat) and AGAUR, Generalitat de Catalunya. (Industrial PhD UPF – Institut Municipal de Persones amb Discapacitat, referència DI 2020 008) IP: Helena Ramalhinho; PhD student: Laura Portell.
- (2020-2022) The social urgency of a growing elderly population: Building sustainable home care services. SR0225 La Caixa Social Research 2019. IP: Jesica de Armas.
- (2019-2021) Logistics Optimization for the Home Health and Social Care Services. Competitive Research Project: RTI2018-095197-B-I00, Ministerio de Ciencia, Innovación y Universidades, Plan Estatal De Investigación Científica y Técnica y de Innovación 2017-2020, Programa Estatal De I+D+I Orientada a los Retos de la Sociedad, Spain. Research director (IP): Helena Ramalhinho Lourenço and Jésica de Armas.
- Mathematical Models and Algorithm to solve Logistics Optimization Problems in SEAT-Volkswagen. Funding: Seat (Spain) and AutoUni Volkswagen (Germany). Industrial PhD Funding: SEAT. IP: Helena Ramalhinho. PhD student: Marcelus Fabri.
- Cost Action “European Network of Collaboration on Kidney Exchange Programmes”, (ENCKEP) CA15210. COST (EU Framework Programme Horizon 2020). IP: Prof. Joris van de Klundert and Prof. David Malone. Spanish MC coordinators: Helena Ramalhinho & Flip Klijn
Relevant recent publications
- Ramalhinho Lourenço, H., Martin, O. and Stützle, T. (2019), Iterated Local Search: Framework and Applications. In Handbook of Metaheuristics, International Series in Operations Research & Management Science 272, Gendreau, J.-Y. Potvin (eds.), Springer International Publishing AG 129-168, DOI 978-3-319-91086-4_5.
- Pagès-Bernaus A., Ramalhinho H., Juan A.A., Calvet L. (2019), Designing E-commerce Supply Chains: a stochastic facility-location approach,International Transactions in Operational Research 26:2, 507-528. DOI: 10.1111/itor.12433.
- Grasas A., Juan, A.A. Faulin, J., De Armas, J. and Ramalhinho H. (2017), Biased Randomization of Heuristics using Skewed Probability Distributions: applications to routing and other problems, Computers & Industrial Engineering 110: 216–228. Doi: 10.1016/j.cie.2017.06.019.
- Coelho V.N., Grasas A., Ramalhinho H., Coelho I.M., Souza M.J.F. (2016), An ILS-based Algorithm to Solve a Large-scale Real Heterogeneous Fleet VRP with Multi-trips and Docking Constraints, European Journal of Operational Research 250 (2): 367–376. doi:10.1016/j.ejor.2015.09.047
- Grasas A., Juan, A.A. and Lourenço H.R. (2016), SimILS: A Simulation-based extension of the Iterated Local Search metaheuristic for Stochastic Combinatorial Optimization, Journal of Simulation 10(1), 69–77 doi:10.1057/jos.2014.25.
- Juan, A. A., Faulin, J., Ferrer, A., Lourenco H.R., and Barros, B. (2013), MIRHA: Multi-start biased randomization of heuristics with adaptive local search for solving non-smooth routing problem. TOP: Volume 21, Issue 1, Pages 109-132. DOI 10.1007/s11750-011-0245-1. Article.
See complete list: Publications