Elisabeth Zehendner

Benefits of a truck appointment system on the service quality of inland transport modes at a multimodal container terminal

The connection of a container terminal to its hinterland is a key area for competition. Therefore, more and more attention is paid to the service quality of inland transport modes such as trucks, trains and barges. An efficient allocation of internal material handling resources and the use of new strategies, such as truck appointment systems, can reduce the time vehicles spend at the terminal. We propose a mixed integer linear programming model, based on a network flow representation of the terminal, to determine the number of appointments to accept per time slot and an allocation of internal resources minimizing service times of trains and barges simultaneously. By comparing container terminals with and without appointment systems, we show that a truck appointment system is beneficial for trucks as well as for trains and barges.

An improved mathematical formulation for the blocks relocation problem

This paper deals with the blocks relocation problem (also called container relocation problem). First, it corrects the binary linear programming model BRP-II presented in Caserta et al. (2012). Second, it improves the initial model formulation by removing superfluous variables, tightening some constraints, introducing a new upper bound and applying a pre-processing step to fix several variables. Computational results show the efficiency of the improved model for small and medium sized instances.

A branch and price approach for the container relocation problem

The objective of the container relocation problem is to retrieve a set of containers from the bay (a part of the yard) of a container terminal in a given order with a minimum number of parasite movements. Up to now, only few exact solution approaches exist for this problem. They are only able to solve small and medium sized instances since the number of variables increases exponentially with the number of containers and the bay size. To overcome this problem, we introduce the first column generation approach for this problem and embed it into a branch and price procedure. We also introduce a new upper bound on the number of relocations based on the values of dual variables. Computational results show that our column generation approach provides a tight gap and solves small and medium instances with a small subset of columns within few iterations. But, the time spent on solving the subproblem prevents solving larger instances. Finding a way to reduce the time spent on the subproblem constitutes the next step of this work.

An algorithm with performance guarantee for the Online Container Relocation Problem

This paper introduces and investigates the Online Container Relocation Problem, where containers have to be retrieved from a bay in a container terminal so as to minimize the number of relocations. Unlike the offline version of the problem, the order of container retrievals is revealed one at a time in an online fashion. We analyze the so-called leveling heuristic using the perspective of worst-case competitive analysis of online algorithms and derive its competitive ratio. We then provide some computational experiments which give insights on the actual average performance of the heuristic.