Modeling an offshore container terminal: the Venice case study

In order to reduce marine transportation times and related costs, as well as the environmental impacts, an alternative multimodal route to the current Suez-Gibraltar-North Sea corridor for the containers shipped from Far and Middle East was identified as potentially very effective. A key operational problem to achieve this result is the capacity and the effectiveness of the terminals within the concerned new logistic chain. In this framework, the Venice Port Authority is developing a project aimed to improve relevantly the potential of its container terminals to al-low loading/unloading of containers to and from the Central Europe. The project includes a new offshore terminal for mooring huge ships (up to 18.000 TEU) in the Adriatic Sea and a link operated by barges with an onshore terminal in Venice to overcome the constraints for the navigation of the containers ships in the Venetian lagoon. This innovative operational scheme requires a deep functional analysis to ensure the full capacity operation, assess the reachable performances and correspondingly dimensioning the required equipment (cranes, barges, quays, etc.). For this purpose, the authors developed a specific discrete-events simulation model. The paper includes the presentation of the model and the results of its application to Venice case study, by identifying the benefits achievable with this approach and the potential wider application fields

National and international freight transport models: overview and ideas for further development

This paper contains a review of the literature on freight transport models, focussing on the types of models that have been developed since the nineties for forecasting, policy simulation and project evaluation at the national and international level. Models for production, attraction, distribution, modal split and assignment are discussed in the paper. Furthermore, the paper also includes a number of ideas for future development, especially for the regional and urban components within national freight transport models

Simulating a physical internet enabled mobility web: the case of mass distribution in France

International audiencePhysical Internet (PI, π) is a novel concept aiming to render more economically, environmentally and socially efficient and sustainable the way physical objects are transported, handled, stored, realized, supplied and used throughout the world. It enables, among other webs, the Mobility Web which deals with moving physical objects within an interconnected set of unimodal and multimodal hubs, transits, ports, roads and ways. We want to develop and use holistic simulations to study and quantify the impact in terms of economical, environmental, and social efficiency and performance of evolving from the current system of freight transportation toward an open logistics web in France. This paper focuses on how the mobility web simulator supporting this study was designed and developed. The simulator produces large-scale simulations of mobility webs consisting of a large number of companies, sites and agents dealing with thousands of daily orders. It supports route and rail transportation modes, pallets and PI-containers for product shipping, different kinds of routing and shipping strategies, and various types of hubs

Benefit-Cost Analysis for Transportation Planning and Public Policy: Towards Multimodal Demand Modeling

This report examines existing methods of benefit-cost analysis (BCA) in two areas, transportation policy and transportation planning, and suggests ways of modifying these methods to account for travel within a multimodal system. Although the planning and policy contexts differ substantially, this report shows how important multimodal impacts can be incorporated into both by using basic econometric techniques and even simpler rule-of-thumb methods. Case studies in transportation planning focus on the California Department of Transportation (Caltrans), but benchmark California’s competencies by exploring methods used by other states and local governments. The report concludes with a list and discussion of recommendations for improving transportation planning models and methods. These will have immediate use to decision makers at Caltrans and other state DOTs as they consider directions for developing new planning capabilities. This project also identifies areas, and lays groundwork, for future research. Finally, by fitting the planning models into the broader context of transportation policy, this report will serve as a resource for students and others who wish to better understand BCA and its use in practice

Sequence-Based Simulation-Optimization Framework With Application to Port Operations at Multimodal Container Terminals

It is evident in previous works that operations research and mathematical algorithms can provide optimal or near-optimal solutions, whereas simulation models can aid in predicting and studying the behavior of systems over time and monitor performance under stochastic and uncertain circumstances. Given the intensive computational effort that simulation optimization methods impose, especially for large and complex systems like container terminals, a favorable approach is to reduce the search space to decrease the amount of computation. A maritime port can consist of multiple terminals with specific functionalities and specialized equipment. A container terminal is one of several facilities in a port that involves numerous resources and entities. It is also where containers are stored and transported, making the container terminal a complex system. Problems such as berth allocation, quay and yard crane scheduling and assignment, storage yard layout configuration, container re-handling, customs and security, and risk analysis become particularly challenging. Discrete-event simulation (DES) models are typically developed for complex and stochastic systems such as container terminals to study their behavior under different scenarios and circumstances. Simulation-optimization methods have emerged as an approach to find optimal values for input variables that maximize certain output metric(s) of the simulation. Various traditional and nontraditional approaches of simulation-optimization continue to be used to aid in decision making. In this dissertation, a novel framework for simulation-optimization is developed, implemented, and validated to study the influence of using a sequence (ordering) of decision variables (resource levels) for simulation-based optimization in resource allocation problems. This approach aims to reduce the computational effort of optimizing large simulations by breaking the simulation-optimization problem into stages. Since container terminals are complex stochastic systems consisting of different areas with detailed and critical functions that may affect the output, a platform that accurately simulates such a system can be of significant analytical benefit. To implement and validate the developed framework, a large-scale complex container terminal discrete-event simulation model was developed and validated based on a real system and then used as a testing platform for various hypothesized algorithms studied in this work