Stefano de Luca

Tactical and strategic planning for a container terminal: Modelling issues within a discrete event simulation approach

Abstract In this paper different microscopic discrete event simulation models for a container terminal are presented. The focus is on the best approach to adopt to simulate handling activity time duration and on which level of detail should be pursued with respect to different planning horizons that a decision maker have to face. The models share the same logical architecture but differ in the approaches pursued to estimate handling activity time duration. Terminal operations were broken down into elementary activities pursuing a level of disaggregation not usual in the literature; time duration of each elementary handling activity was modelled through a stochastic approach, distinguishing container type; validation was carried out with respect to different planning horizons (real-time/short-term, long-term) through the definition of local and global indicators and a before-and-after analysis. Modelling issues are discussed for tactical and strategic planning, and operational guidelines are given.

Stochastic equilibrium assignment with variable demand: Theoretical and implementation issues

Recently, it has been pointed out that transport models should reflect all significant traveler choice behavior. In particular, trip generation, trip distribution, modal split as well as route choice should be modeled in a consistent process based on the equilibrium between transport supply and travel demand. In this paper a general fixed-point approach that allows dealing with multi-user stochastic equilibrium assignment with variable demand is presented. The main focus was on investigating the effectiveness of internal and external approaches and of different algorithmic specifications based on the method of successive averages within the internal approach. The vector demand function was assumed non-separable, non-symmetric cost functions were adopted and implementation issues, such updating step and convergence criterion, were investigated. In particular the aim was threefold: (i) compare the internal and the external approaches; (ii) investigate the effectiveness of different algorithmic specifications to solve the variable demand equilibrium assignment problem through the internal approach; (iii) investigate the incidence of the number of the links with non-separable and/or asymmetrical cost functions. The proposed analyses were carried out with respect to two real-scale urban networks regarding medium-size urban contexts in Italy.

Greening the transportation sector: a methodology for assessing sustainable mobility policies within a sustainable energy action plan

The reducing use of fossil fuels and greenhouse gas emissions is one of the main aims of urban planning. These objectives directly involve urban activities which are responsible for 80% of energy consumption and CO2 emissions and indirectly the transport sector which contributes in the range of 20%–40% in terms of consumption of fossil fuels and emissions of greenhouse gases and particulate matter. In this context, the simulation, the evaluation and the implementation of sustainable mobility policies are a crucial challenge for decision makers and analysts. At this aim, the paper proposes an integrated modelling framework which, following a bottom-up approach, combines a transportation simulation model (demand, supply and supply-demand interaction) with traffic fuel consumption and vehicle emission models. The aim was twofold: 1) specify and implement a modelling framework characterised by a level of detail not usual in literature and able to estimate fuel consumptions and greenhouse gas emissions with respect to any transportation scenario; 2) investigate the effects of different transport policies by applying the system of models. The proposed methodology was implemented to the urban context of Salerno municipality (Southern Italy), within the development of the sustainable energy action plan.

Signal Setting Design at a Single Junction Through the Application of Genetic Algorithms

The purpose of this chapter is the application of Genetic Algorithms to solve the Signal Setting Design at a single junction. Two methods are compared: the monocriteria and the multicriteria optimisations. In the former case, three different objectives functions were considered: the capacity factor maximisation, the total delay minimisation and the total number of stops minimisation; in the latter case, two combinations of criteria were investigated: the total delay minimisation and the capacity factor maximisation, the total delay minimisation and the total number of stops minimisation. Furthermore, two multicriteria genetic algorithms were compared: the Goldberg’s Pareto Ranking (GPR) and the Non Dominated Sorting Genetic Algorithms (NSGA-II). Conclusions discuss the effectiveness of multicriteria optimisation with respect to monocriteria optimisation, and the effectiveness of NSGA-II with respect to the GPR.

Simulating Container Terminal Performances: Microscopic vs. Macroscopic Modelling Approaches

Most of the existing contributions for container terminal analysis follow approaches based on optimization models, that are mainly useful to support strategic decisions about terminal container configuration. Many others contributions follow the simulation approach, which allows a detailed analysis but may lead to computational problems and is rather computer demanding, especially when resulting models are used to support optimization. This paper investigated the prediction reliability of two different approaches to container terminal simulation: microscopic and macroscopic. The former simulating single container movement, the latter simulating container flows movement. The microscopic model was a discrete event simulation model, the macroscopic model was a dynamic discrete time based (space-time) network assignment model. Both modelling approaches were implemented and compared taking advantage of some significant investment made by the Salerno Container Terminal (Italy) between 2005 and 2011. In particular, disaggregate (microscopic) and an aggregate (macroscopic) simulation models implemented in 2005 were validated with a large set of data acquired in 2011 after some structural and functional terminal modifications. Through this analysis it was possible to analyze the prediction reliability of both simulation approaches and to draw some operational guidelines.

Matching macro- and micro-scopic approaches for the evaluation of traffic management impacts

The paper focuses on the evaluation of the combined effect of Traffic Signal Control Strategy (TSC) and Variable Message Sign (VMS). With reference to the TSC a dynamic selection strategy based on macroscopic flow variables was considered for off-line traffic signal plans design. The combination of two ITS solutions, TSC and VMS, was tested through microscopic approach by SUMO traffic simulator which allows to directly reproduce the pollutant emissions and fuel consumptions.

The use of the analytic hierarchy process method for supporting urban road regeneration actions: The case study of Naples

The paper focuses on the application of an AHP (Analytic Hierarchy Process) procedure for helping the decision maker in the identification of the road maintenance actions aiming to improve safety conditions and optimize the interchanges/interactions in terms of origin/destination flows among some strategic areas of the municipality of Naples.

Traditional random utility models vs hybrid choice models for assessing environmental impacts of a new technology: The HySolaKit case study

The aim of the present paper is to investigate if behavioural models which are more accurate and effective (latent variables hybrid choice models) in simulating new automotive technology adoption, may significantly affect market forecasts and environmental impacts estimation. Since the time and the cost to develop each modelling solution are significantly different and require different types of surveys, the main goal of the paper is to give some insights into the costs and the benefits of each solution. Moreover, different models are compared in terms of sensitivity to different market scenarios and in terms of estimated environmental impacts on a real case study (the city of Salerno — southern Italy).

Transportation systems with connected and non-connected vehicles: Optimal traffic control

The paper aims to develop a consistent framework for traffic management allowing for the joint optimization of connected vehicle paths and departure times and of signal control. The procedure is based on the communication between connected vehicles and signal controller (Vehicle to Infrastructure communications). Thus, the optimization procedure is characterized by two steps: the first refers to the adaptive traffic signal optimization, whilst the second refers to the optimization of routes and departure times of connected vehicles. In particular, as regards the adaptive traffic signal control, stage durations and sequences, as well as the node offsets, are considered as decision variables optimized with a scheduled synchronization method based on a meta-heuristic algorithm. On the contrary, the optimization of connected vehicle paths and departure times were considered as decision variables through a Mixed Integer Mathematical Program. Finally, as regards the traffic flow model, a further development of the Cell Transmission Model was considered. The whole framework was tested on a toy network.