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Victor Pillac

dblp:121/5530 · DBLP profile ↗
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3ranked-venue papers
1as first author
0since 2021 · last 2015
0000-0003-3726-8118ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 3 · 1 first-authorGraphics, computer vision, multimedia, augmented reality and games · 2

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Theoretical computer science
1 paper
Mathematical optimization · 100%
Artificial intelligence
1 paper
Planning, search and constraint satisfaction · 77% Multi-agent systems · 23%

Topics — the 3 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Knowledge, reasoning and agents › Planning, search and constraint satisfaction › task planning
evacuation planning
0.212015
Convergent Plans for Large-Scale Evacuations · AAAI 2015
Mathematical optimization
discrete optimization
0.212015
Convergent Plans for Large-Scale Evacuations · AAAI 2015
Mathematical optimization › discrete optimization
mixed integer linear programming
0.212015
Convergent Plans for Large-Scale Evacuations · AAAI 2015

Methods — techniques the papers use, named apart from their topics

two-stage decomposition · 0.4simulation · 0.4mixed-integer programming · 0.2mixed integer programming · 0.2
YearPublicationVenuePosition
2015 Convergent Plans for Large-Scale Evacuations
abstract
Evacuation planning is a critical aspect of disaster preparedness and response to minimize the number of people exposed to a threat. Controlled evacuations aim at managing the flow of evacuees as efficiently as possible and have been shown to produce significant benefits compared to self-evacuations. However, existing approaches do not capture the delays introduced by diverging and crossing evacuation routes, although evidence from actual evacuations highlights that these can lead to significant congestion. This paper introduces the concept of convergent evacuation plans to tackle this issue. It presents a MIP model to obtain optimal convergent evacuation plans which, unfortunately, does not scale to realistic instances. The paper then proposes a two-stage approach that separates the route design and the evacuation scheduling. Experimental results on a real case study show that the two-stage approach produces better primal bounds than the MIP model and is two orders of magnitude faster; It also produces dual bounds stronger than the linear relaxation of the MIP model. Finally, simulations of the evacuation demonstrate that convergent evacuation plans outperform existing approaches for realistic driver behaviors.
Caroline Even, Victor Pillac, Pascal Van Hentenryck
AAAI2
2014 NICTA Evacuation Planner: Actionable Evacuation Plans with Contraflows
abstract
Evacuations are a critical aspect of disaster management, and generally the first prevention measure to ensure the safety of the population under threat. Designing evacuation plans is a complex task that requires to take into account multiple factors in order to limit congestion and ensure that all evacuees reach safety in time. This paper proposes a conflict-based path-generation algorithm for evacuation planning and a web-based intelligent system targeted at local authorities and emergency services. The key contribution of this paper is to propose the first scalable approach to produce actionable evacuation plans that simultaneously schedules the evacuation and selects contraflow roads. The benefits of the approach are illustrated on two large-scale case studies. The resulting optimization model is integrated in NICTA EVACUATION PLANNER, a tool to model, plan, and simulate evacuations.
Caroline Even, Victor Pillac, Pascal Van Hentenryck
ECAI2
2012 An event-driven optimization framework for dynamic vehicle routing
Victor Pillac, Christelle Guéret, Andrés L. Medaglia
Decis. Support Syst.1