RESEARCH
RESEARCH AREAS
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Operations research
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Optimization
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Algorithms
- Logistics
RECENT RESEARCH APPLICATIONS
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Humanitarian logistics
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Urban logistics (sustainable cities)
- Port logistics
Edition : Editor in Chief of the Cahiers de la logistique
MAIN RESEARCH TOPICS
I have been interesting and contributing since 2010 on solving optimization problems in the aftermath of natural disasters. Most of the problems relies on network design, scheduling, vehicle routing, location, and some integrated ones. Two major issues are shared in such studies: (i) the problems have been addressed in a large scale, and (ii) realistic data of urban areas is used in the numerical experiments. As a consequence, several interesting analyses and insights have been obtained.
More recently, I am working on other type of crises such as industrial disasters and health crises like the one of the COVID-19.
My research on this topic starts in 2022 and mainly covers smart and sustainable port activities. I am currently investigating fundamental issues of transportation and inventory problems, considering more sustainable strategies. Useful circular maritime transportation routes are considered, keeping circular routes, but using a new strategy to reduce the consumption and as a consequence the emissions.
In this context, I have studied from 2013 to 2019, the network design and the scheduling of disruptions, either predictable (road works, maintenance, social events, etc.) or unplanned (accidents, bad weather conditions, disasters, etc), on urban road networks. For the former, the idea is to reconfigurate the urban network in order to deviate the flow of vehicles by alternative paths. For the latter, the problems couple the network design to the scheduling of predictable disruptions. The approches developed are centralized and take into account several graph theory aspects such as connectivity, strong connectivity and arc reversals.
From 2012 to 2015, I have also worked on robust optimization, mainly on the development of generic methods (e.g. scenario-based heuristics, primal-dual and Benders-based algorithms, metaheuristics) able to solve several robust optimization problems. Such methods have been tested using the following class of problems: the restricted robust shortest path problem and the robust set covering problems. In terms of objective function, I have addressed basicaly the min max regret one.