[Defended thesis] Gabriel Volte: Interactive exact optimisation for numerical services to agriculture

Gabriel is one of the #DigitAg co-funded PhDs

Gabriel defended his thesis on Friday 10th December at 2pm @ Lirmm

Interactive exact optimisation for numerical services to agriculture

  • Start Date: October 2018
  • University:  University of Montpellier
  • PhD School: I2S  – Information Structures Systèmes
  • Field(s): Computer Sciences
  • Doctoral Thesis Advisor(s): Rodolphe Giroudeau, Université de Montpellier, Lirmm and Olivier Naud, Inrae, Itap
  • Funding: #DigitAg – University of Montpellier
  • #DigitAg: Axis 6 – Challenge 5

Abstract: The trend towards a precise, numerical, and data intensive agriculture brings forward the need to integrate in a unique decision support methodology optimization techniques that are efficient, interactive, robust and adaptable. We propose to develop a decision calculus strategy for the management of agricultural activity that combines the efficiency and precision of optimisation methods based on linear integer programming and heuristics, and the flexibility and modularity of constraint programming methods. With the perspective that custom decision support services should be offered to farmers, we make the hypothesis that historics of data, as well as daily updates of informations such as meteorology, crop evolutions and traceability informations should be available. This hypothesis allows for studying strategies that combine off-line (back office) approaches for searching best production processes that meet farmer criteria, and on-line (front office) approaches to contextualize and adapt solutions. We also make the hypothesis that distributed computing platforms could collaborate on calculus and numerical studies will be conducted on this topic, using available data and web services.

In fine, the methodology should integrate stochastic features because of the uncertainties of agricultural production. A first characterization and evaluation of solutions for the current decision period can be based on models built from data historics. In a second step, it is planned to make use of probability estimators linked to meteorological forecast to offer robustness oriented interactivity to the user of decision support tool and decision maker.


Download the thesis manuscript

Papers at international conferences:

  • Gabriel Volte, Eric Bourreau, Rodolphe Giroudeau, Olivier Naud (2019) Differential Harvest Problem, 20ème congrès annuel de la société Française de Recherche Opérationnelle et d’Aide à la Décision (ROADEF 2019)
  • Gabriel Volte, Eric Bourreau, Rodolphe Giroudeau, Olivier Naud (2019) Column generation approach for the Differential Harvest Problem a parametric study, 12th European Federation for Information Technology in Agriculture, Food and the Environment (EFITA), Rhodes island, Greece, 27-29 June, 2019.

Contact:   gabriel.volte [AT] lirmm.fr – +33 4 67 41 85 85