T his paper considers the problem of assigning flights to airport gates. We examine the general case in which an aircraft serving a flight may be assigned to different gates for arrival and departure processing and for optional intermediate parking. Restrictions to this assignment include gate closures and shadow restrictions, i.e., the situation in which certain gate assignments may cause the blocking of neighboring gates. The objectives include maximization of the total assignment preference score, minimization of the number of unassigned flights during overload periods, minimization of the number of tows, as well as maximization of the robustness of the resulting schedule with respect to flight delays. We are presenting a simple transformation of the flight-gate scheduling (FGS) problem to a graph problem, i.e., the clique partitioning problem (CPP). The algorithm used to solve the CPP is a heuristic based on the ejection chain algorithm by Dorndorf and Pesch [Dorndorf, U., E. Pesch. 1994. Fast clustering algorithms. ORSA J. Comput. 6 141-153]. This leads to a very effective approach for solving the original problem.
Transshipment yards, where gantry cranes allow for an ecient transshipment of containers between dierent freight trains, are important entities in modern railway systems and facilitate the general shift from point-to-point transport to hub-and-spoke railway systems. Modern rail-rail transshipment yards accelerate container handling, so that multiple smaller trains with equal destination can be consolidated to a reduced number of trains without jeopardizing on time deliveries. An important problem continuously arising during the daily operations of a transshipment yard is the train scheduling problem, which decides on the succession of trains at the parallel railway tracks. This problem with a special focus on resolving deadlocks and avoiding multiple crane picks per container move is investigated within the paper on hand. A mathematical program along with a complexity proof is provided and exact (Dynamic Programming) and heuristic (Beam Search) procedures are described.
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