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MOGISA Group

MOGISA Group . Modeling, Optimization, and Integrated Management of Systems of Activities Toulouse, France. LAAS = L aboratory for A nalysis and A rchitecture of S ystems Founded in 1967 Laboratory of the French National Center for Scientific Research (CNRS) Associated to:

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MOGISA Group

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  1. MOGISA Group Modeling, Optimization, and Integrated Management of Systems of Activities Toulouse, France MOGISA

  2. LAAS = Laboratory for Analysis and Architecture of Systems Founded in 1967 Laboratory of the French National Center for Scientific Research (CNRS) Associated to: Université Paul Sabatier (UPS) Institut National Polytechnique (INP) Institut National des Sciences Appliquées (INSA) Institut Supérieur de l’Aéronautique et de l’Espace (ISAE) More than 650 persons: Research scientists ( 100) Faculty members ( 100) Graduate, PhD students, and postdocs ( 300) Engineers, technicians, and administrative clerks ( 100) 4 thematic research areas: Micro and Nano Systems (MINAS) Modelling, Optimisation and Control of Systems (MOCOSY) Robotics and Artificial Intelligence (RIA) Critical Computer Systems (SINC) LAAS-CNRS MOGISA

  3. Decision and Optimization theme • Discrete and continuous optimization • Constraint satisfaction • Performance evaluation • Robust, non-linear, saturated control • Model-based diagnosis • 3research teams: • DISCO (diagnosis, supervision) • MAC (control) • MOGISA (discrete optimization, discrete-event dynamic systems) MOGISA

  4. Research scientists BRIAND Cyril (Pr) ESQUIROL Patrick (Mcf) HEBRARD Emmanuel (CR) HOUSSIN Laurent (Mcf) HUGUET Marie-José (Mcf) JOZEFOWIEZ Nicolas (Mcf) LOPEZ Pierre (DR) MERCE Colette (Pr) MONCEL Julien (Mcf) NGUEVEU Sandra (Mcf) Secretary MOUCLIER Christèle MOGISA: Members (February 15, 2012) 11 research scientists –8PhD students – 1 post-docs • Head:ARTIGUES Christian (DR) • PhD Students (year of defence) • CHABAANE Nadia (2015) • BEN RAHHOU Touria(2013) • GAOUA Yacine(2014) • MALTA Leonardo (2015) • SARPONG Boadu(2013) • SIALA Mohamed (2014) • TANGPATTANAKUL Panwadee(2013) • TROJET Mariem(2013) • Post-doc • SIMONIN Gilles MOGISA

  5. Scientific objectives • Research domains • Operations Research • Artificial Intelligence (Constraints) • Control Theory (Discrete-Event Systems) • Research topics • Discrete optimization & Constraint satisfaction • Supply chain management • Scheduling • Transportation • General stakes • Advances (models, algorithms, general methods) for fundamental problems • Tackling complex constraints and multiple objectives for real-world applications • Coping with uncertainty and dynamics MOGISA

  6. Discrete Optimization and Constraint Satisfaction • Objectives • General methods for solving: • NP-hard discrete optimization problems min f(x) xX • NP-complete satisfaction problems x, D(x)  C • Results • Tree search enhanced with learning mechanisms • Tree-based local search: discrepancy search improvements • Large neighborhood search embedding implicit enumeration • Constraint propagation-based cutting planes for integer programming • Applications to industrial problems • Frequency assignment in telecommunications • Production scheduling, project management, supply chain management, passenger transportation… MOGISA

  7. Discrete Optimization and Constraint Satisfaction: trends • Robust discrete optimization • Problems computationally challenging and currently intractable even for small instance problems • New constraint & integer programming approaches • Application for robust scheduling (facing to limits of interval representation for uncertainty of data) • Multi-objective optimization • Exact methods • MIP as search components • Matheuristics (e.g., local branching) • Constraint propagation and satisfaction • Methods hybridization, integration and cross-fertilization for discrete optimization pbs • From CP, SAT, MIP, Metaheuristics, Mach. Learning, Parameterized Complexity MOGISA

  8. Scheduling • Objectives • Integrating complex constraints from real-world applications and tackling uncertainty • Results • Complexity results on open problems • Branch-and-bound methods for complex shop problems • New MIP formulations (OMSP, RCPSP) • Generalized resource constraint propagation • New approach to generate flexible solutions for robust scheduling • Applications to industrial problems • wafer manufacturing • crew scheduling MOGISA

  9. Scheduling: trends • New challenges • Parallel processors • Resource flexibility in production systems • Power management systems • Energy • New efficient (exact and approximate)methods for • cyclic scheduling problems under resource constraints • scheduling under alternatives • multi-objective scheduling • mathematical models and constraint propagation approaches for energy constraints & objectives • (max,+)algebra for solving and for performance evaluation of schedules 3 MOGISA

  10. Robust scheduling • Cooperation vs. Robustness (ROBOCOOP) • Tasks are distributed among a set of agent • Agent schedules are robust • Distributed and reactive scheduling: • Negotiation between Agents • Convergence of negotiations in finite time • Trade-off between global and local objectives • Cooperation mechanisms • Robust scheduling for innovative projects • Problem • Activity failure implies project failure • Past project investments are definitively lost • Alternative activities exist (flexibility): if an activity fails, but one alternative activity succeeds, project can go on • Decision variables • Determine which activities have to be launched and their start time • Objectives • Investments minimization • Risk of project failure minimization (robustness) MOGISA

  11. Railway tracks examination • Waste collecting Land transportation • Objectives • Solving complex Vehicle Routing / Passenger Transportation Problems • Results: New models and methods for • Generalized TSPs • Multi-objective VRPs • VRP with route balancing • Bi-objective TSPs with accessibility • VRPs on multi-graphs • Unusual objectives: stability • Large Arc Routing Problems • Applications MOGISA

  12. Land transportation: trends Goal Convergence toward more realistic problems Optimization of individual/public transports Challenges Multi-modality in passenger transportation and VRPs Advance the use of multi-objective optimization Problems with many constraints (“rich”) Dynamicity Take into account the human side of problems Applications Door-to-door service network (ANR + DHL) High-capacity and real-time on-demand transportation Multi-modal algorithms for GIS MOGISA

  13. Optimization in space • ROSETTA/MOST (Post-doc – CNES Contract) • Scheduling of scientificexperiences • Data transfer management system • Limited energy MOGISA

  14. Optimization in space • Image-takingScheduling of Earth observation satellites (PhDthesisTHEOS Operational Training Program+ Project CNES + Astrium/ONERA on flexible scheduling) MOGISA

  15. Optimization in space • Frequency allocation for satellite communications (Collaboration with Thales AS) MOGISA

  16. Contracts & collaborations • Industrialcontracts : EADS, Airbus, Thales, Astrium, CNES, SNCF, Amadeus • Academic projects • Local and National collaborations • IMT, LARA/ENAC, CLLE/LTC • IBM/ILOG, INRIA Lille-Nord Europe, LAMSADE, LAGIS/ECL, LAPS Bordeaux, LI Avignon, LI Tours, LIMOS, LISA Angers, LOSI Troyes, LIP6,… • Internationalcollaborations : Spain, Canada, Belgium, Germany, Tunisia, Algeria … MOGISA

  17. Other visibility • Involvement in life of ROADEF (French OR&DA society) http://www.roadef.org/ http://www2.lifl.fr/PM2O/ http://challenge.roadef.org/ http://roadef2010.fr/ • Reporting (CRSNG Canada, ECOS-Sud/Nord, FWO Belgium, ANR, ANRT, “Régions”…) • Program committees of conferences (IESM, ILS, MISTA, MOSIM, ROADEF, JFPDA, CIGI) • Conference organization : ROADEF 2010, JFPC 2012, Odysseus 2015 MOGISA

  18. Publications 01/2005-12/2010 • 40 journals with review board • 2 books (editor) • 80 refereed conferences with proceedings • 11 book chapters • 15 PhD thesis • 2 “HDR” MOGISA

  19. What do wewish to develop ? • Multiobjectiveoptimization • New methods • Parallelization to overcomecomputationalcomplexity • Applications • Optimizationunderuncertainties • Robustoptimization • Stochasticprogramming • Collaborative logistics • Intermodal transportation • Integratedsystems MOGISA

  20. MOGISA Group Modeling, Optimization, and Integrated Management of Systems of Activities November, 2011 MOGISA

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