Capita selecta – Logistics Planning: from strategic to real-time


Date(s) for this course will be announced approximately two months before the start of the semester.


10.00 – 16.00 h




Dr. Shadi Sharif Azadeh & Dr. Yousef Maknoon




0.5 (attendance only) / 2 (attendance + passing the assignment)

Course fee:

free for TRAIL/Beta/OML/ERIM members, others please contact the TRAIL office


Dealine: 14 May 2021

For a place on the waiting list, please send an e-mail to


The aim of this course is to tackle several logistics problems in tactical, strategic and operational levels. We aim at solving real case problems in the presence of uncertainty. We address real-time decision-making process for on-demand logistic systems. We investigate the integration of behavioral models in the OR framework and offer tractable resolution approaches to solve them. We explain the concepts, mathematical models and we offer resolution approaches for each proposed topic.

Course description:

  1. Network design and facility location problem
  2. Service network design problem
  3. Integrating behavioral models in optimization framework in the context of transport and mobility. Tackling stochasticity via scenario definitions and simulation-based optimization, as well as using decomposition methods to solve large scale problems.
  4. On-demand logistics.


Students will work on two assignments in groups of 2 or 3. They are required to develop a conceptual framework, formulate their problem, introduce a resolution approach, discuss about their modeling decisions and their limitations and finally provide results and discussions.


The detailed plan of the course and the list of materials will be shared via email during the last week of May.



Discrete optimization, heuristics, metaheuristics, decomposition methods, simulation, uncertainty, sensitivity analysis, approximation algorithms.

Course material:


Knowledge of operations research, knowledge in programming (e.g., Python, C++, Java) and being familiar with using CPLEX or Gurobi.

Pre-registration form

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