Jan Kaffka

Modeling of handling task sequencing to improve crane control strategies in container terminals

Free space to expand the handling area in a container terminal is often not available. Therefore terminal operators have to improve operating strategies to increase the capacity of the terminal. For this purpose the authors developed a handling task sequencing strategy with a priority number for a multi crane module in a container terminal. In this paper this control strategy is compared with other state of the art control strategies to find out which crane control strategy is the best strategy for a container terminal. State of the art strategies only consider terminal specific requirements like travel time improvement, but a container terminal is also subject to market requirements such as short waiting times of the vehicles. Those requirements for terminals are often different so that a handling task sequencing is required which can be adjusted to the specific needs of a terminal.

Development of priority rules for handlings in inland port container terminals with simulation

A container terminal is a complex system with many subsystems, for example stacking area, cranes and vehicles, and a large number of decisions for each subsystem. Due to the interactions of these subsystems, there is a lot of stochastic influence and interdependencies within the decisions, which make an optimized operation of a whole container terminal very complex and without technical and methodical support hard to handle. One optimal operated subsystem influences all other subsystems and therefore does not result in an optimality for the whole system. To optimize the operations in an overall system with all its stochastic influence and interactions the method of simulation is used in this paper, which provides the opportunity to create an experimental model and identify the best recommended course of action. The Institute of Transport Logistics developed the simulation suite ContSim, which permits the modelling and simulation of material and information flows in a container terminal. ContSim provides the possibility to model a terminal on a microscopical layer. All handling and controlling processes of the terminal can be modelled and parameterized.

Impact of different unloading zone locations in transshipment terminals under various forklift dispatching rules

Operators of less-than-truckload terminals face the challenge of improving their efficiency to reduce handling costs and increase the performance of the terminal due to small profit margins. This paper uses material flow simulation to address the impact of different operational levers on a forklift-based internal transportation system. For a given I-shaped terminal two concepts of locating unloading zones are compared and evaluated concerning travel time of forklifts. In addition, different dispatching rules for the forklifts are implemented to reduce the empty travel time of the forklift and identify the potential for improvement based on a distance-optimized fleet control.

Revealing gaps in the material flow of inland port container terminals alongside the danube with simulation

Central European inland waterways are presently utilized way below their theoretical carrying capacity. For instance, cargo transported on the Danube is only 10-20% of that transported on the Rhine. To support an increase of transport flows on inland waterways (especially container transport on the Danube) and to contribute to a significant modal shift from road to waterways, operators have to be enabled to improve their economic position by improving the material flow in the handling points of the intermodal transport chain, container terminals, which oftentimes form a considerable bottleneck due to e.g. long processing times. In this paper, gaps in the material flow of container terminals alongside the Danube are revealed with the use of simulation. The Simulation enables the terminal operator to create an experimental model and decide on the best recommended course of action.

Determination of GHG-Emissions of Handling Operations in Multimodal Container Terminals

The assessment of emissions caused by logistics operations in general and their allocation to individual customers is a major challenge for logistics service providers. Presently, numerous standards and guidelines exist (e.g. ISO 14064-1, ISO 14065, DIN EN 14040, DIN EN 14044, DIN EN 16258, PAS 2050) for the calculation of GHG-emissions caused by logistics processes. Due to missing or incomplete approaches, the assessments as well as regular updates are quite expensive and time-consuming. This endangers in particular the competitiveness of small and medium-sized (sme) logistics service providers who—in the end—need to gather and provide the relevant information for their clients. To support sme-logistics services providers by calculating and allocating GHG-emissions, a CO2-method kit has been developed, which was implemented in MS Excel. This method kit consists of various demonstrator-tools for each mode of transport and stationary processes in logistics systems. Even complex transport chains can be illustrated with this CO2-method kit as well. Overall, the method kit offers a pragmatic solution for everyday business. The underlying calculation methods determine the energy consumption, CO2- and CO2-emissions, distinguished between Well-to-Tank (WtT) and Tank-to-Wheel (TtW). These are part of a Well-to-Wheel (WtW)–Analysis. Aim of this analysis is to express global environmental impacts in CO2-Equivalents—considering the extraction of resources and the usage of fuel (Brinkman et al. 2010). Based on the resulting greenhouse gas values, logistics companies can now identify and carry out appropriate measures to reduce their CO2-emissions. The existing method kit is currently extended to include the determination of GHG-emissions of handling operations in multimodal container Terminals. An in-depth analysis of terminal handling operations and influencing factors on resource energy consumption was needed to develop the CO2-method kit extension. As a first step, the layout and load data were analyzed to picture the terminal as well as the distribution of job orders for the observed period. In addition, crane cycle were deconstructed into sub-processes and transferred into standard processes. Container, weight and distance classes were defined for the assessment of the power consumption data. The power consumption data was collected by measurement devices attached directly to the cranes. In course of the evaluation the measured values were accurately assigned against the crane movements and processed orders in the period under review. Finally, average energy consumption values for handling cycles were determined for the defined container and distance classes, based on selected indicators.

Anwendungsfelder für Optimierungsmodell Optimierungsmodell Anwendungsfelder e

Als einleitendes Anwendungsfeld wird in Unterkapitel 22.1 zunachst das Konzept der Gebietszuordnung thematisch abgegrenzt, dessen Anwendungsbereiche vorgestellt und bekannte Verfahren bewertet. In Unterkapitel 22.2 erfolgt dann eine Einfuhrung in die strategische Netzplanung von Hub-and-Spoke-Netzwerken. Unterkapitel 22.3 stellt aufbauend auf den Grundlagen zur Tourenplanung Eroffnungsverfahren und weiterfuhrende Verbesserungsverfahren vor und erlautert praxisrelevante Nebenbedingungen. In Unterkapitel 22.4 wird aufgezeigt, welchen Einfluss unterschiedliche Transportkostenstrukturen auf die Optimallosungen von Transportproblemen haben. Abschliesend stellt Unterkapitel 22.5 die Untersuchung und Optimierung logistischer Anlagen mit Hilfe ereignisorientierter Simulation vor, Anwendungsfelder sind dabei Umschlaganlagen des Strasenguterverkehrs sowie des Kombinierten Verkehrs.

Anwendungsfelder für Optimierungsmodelle

Als einleitendes Anwendungsfeld wird in Unterkapitel 22.1 zunachst das Konzept der Gebietszuordnung thematisch abgegrenzt, dessen Anwendungsbereiche vorgestellt und bekannte Verfahren bewertet. In Unterkapitel 22.2 erfolgt dann eine Einfuhrung in die strategische Netzplanung von Hub-and-Spoke-Netzwerken. Unterkapitel 22.3 stellt aufbauend auf den Grundlagen zur Tourenplanung Eroffnungsverfahren und weiterfuhrende Verbesserungsverfahren vor und erlautert praxisrelevante Nebenbedingungen. In Unterkapitel 22.4 wird aufgezeigt, welchen Einfluss unterschiedliche Transportkostenstrukturen auf die Optimallosungen von Transportproblemen haben. Abschliesend stellt Unterkapitel 22.5 die Untersuchung und Optimierung logistischer Anlagen mit Hilfe ereignisorientierter Simulation vor, Anwendungsfelder sind dabei Umschlaganlagen des Strasenguterverkehrs sowie des Kombinierten Verkehrs.

Anwendungsfelder für OptimierungsmodellOptimierungsmodellAnwendungsfeldere

Als einleitendes Anwendungsfeld wird in Unterkapitel 22.1 zunachst das Konzept der Gebietszuordnung thematisch abgegrenzt, dessen Anwendungsbereiche vorgestellt und bekannte Verfahren bewertet. In Unterkapitel 22.2 erfolgt dann eine Einfuhrung in die strategische Netzplanung von Hub-and-Spoke-Netzwerken. Unterkapitel 22.3 stellt aufbauend auf den Grundlagen zur Tourenplanung Eroffnungsverfahren und weiterfuhrende Verbesserungsverfahren vor und erlautert praxisrelevante Nebenbedingungen. In Unterkapitel 22.4 wird aufgezeigt, welchen Einfluss unterschiedliche Transportkostenstrukturen auf die Optimallosungen von Transportproblemen haben. Abschliesend stellt Unterkapitel 22.5 die Untersuchung und Optimierung logistischer Anlagen mit Hilfe ereignisorientierter Simulation vor, Anwendungsfelder sind dabei Umschlaganlagen des Strasenguterverkehrs sowie des Kombinierten Verkehrs.