Contributed Session Fri.2.MA 042

Friday, 13:15 - 14:45 h, Room: MA 042

Cluster 13: Logistics, traffic, and transportation [...]

Optimization in logistics


Chair: Julia Funke



Friday, 13:15 - 13:40 h, Room: MA 042, Talk 1

Markus Frey
Column generation for planning the outbound baggage handling at airports

Coauthors: Christian Artigues, Rainer Kolisch


At airports, incoming bags are directed via the baggage handling system to handling facilities, where ground handlers load incoming bags into containers. We present a mixed-integer program scheduling flights' handling period and assigning them to handling facilities. The objective is to minimize the maximal workload of all handling facilities. As the problem exhibits great symmetry, leading to high computation times for branch-and-bound algorithms, the problem is decomposed in several subproblems, reducing symmetry effects. The problem is solved by means of column generation. To further reduce the solution space, dominance criteria are applied.



Friday, 13:45 - 14:10 h, Room: MA 042, Talk 2

Armin F├╝genschuh
Scheduling and routing of fly-in safari airplanes

Coauthors: George Nemhauser, Yulian Zeng


The scheduling and routing of small planes for fly-in safaris is a challenging planning problem. Given a fleet of planes and a set of flight requests with bounds on the earliest departure and latest arrival times, the planes must be scheduled and routed so that all demands are satisfied. Capacity restrictions on the loads and fuel also must be satisfied. Moreover the refueling of the planes, which can only be done in certain locations, must be scheduled. We present a mixed-integer linear programming based formulation for this problem. For its solution we develop a primal heuristic based on randomized local search. Using a branch-and-cut solver, the MILP formulation can be solved to proven optimality only for small instances. To achieve better dual bounds we present a set-covering based reformulation, where new columns are generated on demand by heuristics and exact methods. We also present a reformulation where the time windows are relaxed, and later reintroduced by cutting planes and branching. Numerical results on real-world instances show the computational merits of our approaches.



Friday, 14:15 - 14:40 h, Room: MA 042, Talk 3

Julia Funke
A mixed integer program for a variant of the truck and trailer routing problem with time windows


The formal problem we consider comes from a logistic yard background. Containers are located in a yard and have to be moved at certain times, e.g., from a storage area to a production line and then later back to a pick-up area or to an external site. For these operations a pool of truck units and special trailers is available. The tasks should be fulfilled within certain time windows at the least possible cost.
Our approach is to define this problem as a mixed integer program and solve it with the MIP-solver SCIP. We define two networks one for truck flows and one for trailer flows. We couple the shared decisions so that the optimization model persists of one problem.


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