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Data, Uncertainty and Optimization

Scientific and technical environment of the training course

Centre international de rencontres mathématiques - UMS 822

COURSE DIRECTOR

Patrick FOULON

Senior researcher

UMS 822

LOCATION

MARSEILLE (13)

ORGANISATION

3 days - From 4 to 12 attendees
Training course in English

Onsite accommodation (at Cirm - Scientific and conference centre) is strongly encouraged in order to benefit from all exchanges taking place during the day and in the evening.
Contact: interface@cirm-math.fr

TRAINING FEES

1600 Euros

AT THE END OF THE TRAINING COURSE

Satisfaction survey from trainees
A certificate of attendance is delivered.

COURSE DATE

17420 : from tuesday 28/11/2017 to thursday 30/11/2017

January February March April
May June July August
Sept. Oct. Nov.
17420
Dec.

OBJECTIVES

- Learn and know how to put into practice representation methods of uncertainties adapted to the formulation of problems in multi-stage stochastic optimization
- Learn and know how to put into practice methods of numerical resolution

PUBLICS

Researchers and engineers working in energy, transport, finance, etc.
Attendees are invited to download and fill the survey from our web site to adapt the programme to their expectations.

PRE-REQUIREMENT

- Knowledge of basic continuous optimization: linear programming, convexity, first-order optimality conditions
- Attendees should master the Scicoslab software (free).

TRAINING PROGRAMME

Data is abundant: energy demand, transport and mobility demand, environmental indicators, meteorological conditions are a few examples where data is available. How can decision-makers incorporate such data when they have to address investment strategies (network extension, new technologies)? How can engineers manage operations - transport network control, smart grid regulation - taking advantage of the available information? These are the type of questions addressed in the Interface Programme Couse on Data, Uncertainty and Optimization.

- Two-stage stochastic programming
- Scenario generation
- Progressive hedging
- Multi-stage stochastic dynamic programming
- Examples of case studies
- Workshop on industry case studies

Click HERE for detailed programme.

This 3-day training session alternates courses, case studies and computer sessions.

At the end of the 3-day training session, participants will be invited to attend an Academic workshop in the morning of Friday 1st December 2017.

EQUIPMENT

Participants should bring their own laptop, equipped with the Scicoslab software. Computers will be also available onsite for those without a laptop.

SPEAKERS

P. Carpentier (Professor), J-P Chancelier, M. De Lara and V. Leclère (Researchers)

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