Marco Caserta received his Ph.D. in Industrial Engineering and Operations Research from the University of Illinois (USA), after earning a MSc in Management Engineering from the Politecnico di Milano (Italy). Prior to joining IE, Marco has held faculty positions at Hamburg University, Germany, Tecnológico de Monterrey, Mexico, and the University of Illinois, USA. He teaches statistics at IE University and optimization related courses at IE Business School.

His main research interest is focused on the design and development of metaheuristic-based algorithms for very large scale real-world optimization problems, with a special focus on data mining, logistics, telecommunication, and transportation related problems. He has published a number of papers in international journals in the area of operations research/management science.


• Habilitation (venia legendi) in Business Administration, Hamburg University, Germany

• Ph.D. in Operations Research, University of Illinois, Chicago, USA

• M.S. Management Engineering, Politecnico di Milano, Italy

• Bachelor in Management Engineering, Politecnico di Milano, Italy


• Professor of Statistics, IE University, Spain, from 2013

• Adjunct Professor, IE Business School, Spain, 2010-2013

• Postdoc Hamburg University, Germany, 2007-2011

• Professor, Tecnológico de Monterrey, Mexico, 2004-2007

• Lecturer, University of Illinois, USA, 2003-2004


• Consultant in Optimization, Goal Systems, Spain, 2004


  • Caserta, M. & Voss, S. (2019). “The robust multiple-choice multidimensional knapsack problem”. Forthcoming in Omega International Journal of Management Science
  • Caserta, M.& Reiners, T. (2016). “A pool-based pattern generation algorithm for logical analysis of data with automatic fine-tuning”. European Journal of Operational Research, Vol. 248(2): 593–606
  • Caserta, M.& Voß, S. (2016). “A corridor method based hybrid algorithm for redundancy allocation”. Journal of Heuristics, Vol. 22(4):405–429
  • Caserta, M.& Voß, S. 2015). “A discrete-binary transformation of the reliability redundancy allocation problem”. Mathematical Problems in Engineering, Vol. 2015: 1–6