Lukas Glomb

A novel Pareto-optimal cut selection strategy for Benders Decomposition

  • Lukas Glomb
  • Frauke Liers
  • Florian Rösel
    • Categories (Mixed) Integer Linear Programming Tags ,

    Decomposition methods can be used to create efficient solution algorithms for a wide range of optimization problems. For example, Benders Decomposition can be used to solve scenario-expanded two-stage stochastic optimization problems effectively. Benders Decomposition iteratively generates Benders cuts by solving a simplified version of an optimization problem, the so-called subproblem. The choice of the generated … Read more

    Fleet & tail assignment under uncertainty

  • Lukas Glomb
  • Frauke Liers
  • Florian Rösel
    • Categories (Mixed) Integer Linear Programming, Airline Optimization, Robust Optimization Tags , , ,

    Airlines solve many different optimization problems and combine the resulting solutions to ensure smooth, minimum-cost operations. Crucial problems are the Fleet Assignment, which assigns aircraft types to flights of a given schedule, and the Tail Assignment, which determines individual flight sequences to be performed by single aircraft. In order to find a cost-optimal solution, many … Read more

    A novel decomposition approach for holistic airline optimization

  • Lukas Glomb
  • Frauke Liers
  • Florian Rösel
    • Categories Airline Optimization, Applications - OR and Management Sciences Tags , , , ,

    Airlines face many different planning processes until the day of operation. These include Fleet Assignment, Tail Assignment and the associated control of ground processes between consecutive flights, called Turnaround Handling. All of these planning problems have in common that they often need to be reoptimized on the day of execution due to unplanned events. In … Read more

    A rolling-horizon approach for multi-period optimization

  • Lukas Glomb
  • Frauke Liers
  • Florian Rösel
    • Categories Airline Optimization, Applications - OR and Management Sciences, Production and Logistics Tags , , , ,

    Mathematical optimization problems including a time dimension abound. For example, logistics, process optimization and production planning tasks must often be optimized for a range of time periods. Usually, these problems incorporating time structure are very large and cannot be solved to global optimality by modern solvers within a reasonable period of time. Therefore, the so-called … Read more