Maurizio Bielli

GENETIC ALGORITHMS IN BUS NETWORK OPTIMIZATION

This paper focuses on a new method to compute fitness function (ff) values in genetic algorithms for bus network optimization. In the proposed methodology, a genetic algorithm is used to generate iteratively new populations (sets of bus networks). Each member of the population is evaluated by computing a number of performance indicators obtained by the analysis of the assignment of the O/D demand associated to the considered networks. Thus, ff values are computed by means of a multicriteria analysis executed on the performance indicators so found. The goal is to design a heuristic that allows to achieve the best bus network satisfying both the demand and the offer of transport.

Object oriented model for container terminal distributed simulation

In shipping port sector, containers are the most dynamic and complex to manage. To provide adequate strategy for the increasing traffic, ports must either expand facilities or improve efficiency of operations. In investigating ways in which ports can improve efficiency, this paper outlines a container terminal simulation model and gives components architecture that are implemented with Java. Simulator calibration and validation are also presented in the paper. The main goal of the present work is to provide a help tool in a port decision support system. The object oriented software design using UML diagrams is deployed in this project.

Object modeling and path computation for multimodal travel systems

Abstract This paper describes a multimodal travel system (MTS) designed to address the needs of a variety of demand-responsive transport. An origin–destination ( O – D ) trip in transportation network can be accomplished by using multiple modes. In urban network passengers may boarding buses or metros to go from one place to another, and modes as autobus or trains are used by passengers to travel between cities. The work focuses on the network object modeling and multimodal shortest path algorithm. A solution to the problem of long-run planning of transit on multimodal network has been implemented and tested. The work presents the general results found, and the proposed algorithm recognizes the set of constraints related to the time schedule and the sequence of used modes in a O – D trip. The aim is to provide a tool for detecting the facilities of using different travel modes through a transportation network. Routings may include distinct combination of rail, and route. Geographic Information Systems (GIS) were invaluable in the cost-effective construction and maintenance of this work and the subsequent validation of mode sequences and paths selections. Attention is devoted to the multimodal path operator as well as to the use of GIS-transit planning.

A heuristic procedure for the crew rostering problem

Abstract This paper deals with the problem of planning work schedules in a given time horizon so as to evenly distribute the workload among the drivers in a mass transit system. An integer programming formulation of this problem is given. An iterative heuristic algorithm is described which makes use of a lower bound derived from the mathematical formulation. Furthermore, the algorithm at each iteration solves a multilevel bottleneck assignment problem for which a new procedure that gives asymptotically optimal solutions is proposed. Computational results for both the rostering problem and the multilevel bottleneck assignment problem are given.

System Aspects and Optimization Models In ATC Planning

The current Air Traffic Control (ATC) systems are mainly conceived to ensure safety of flights and orderly operations, according to procedures and international rules. So, they are essentially tactical ground-based systems operated by human controllers. performing manually many relevant functions with short term interventions.

A DSS approach to urban traffic management

Abstract Urban traffic management is a continuous decision process of coordination of all the individual elements (traffic signals, arterial roads, traffic, parking) and the interrelated components of urban transport (private cars, transit, pedestrians, etc.). Its aim is the achievement of maximum efficiency and productivity for the whole system through the application of operating, pricing, regulatory and service policies. For this purpose, many different specific problems have been addressed and several models developed according to the classical system engineering approach. However, the complexity of urban traffic systems and the presence of a large number of conflicting goals and objectives postulated by various groups emphasizes the need for a DSS approach in this field. Thanks to this approach, the integration of different methods and techniques (e.g. Operations Research and Artificial Intelligence) and the effective support of public decision making could be obtained. Moreover, the approach and the scenario considered must also take into account the needs arising from the introduction of new information technologies and strategies in urban transport systems, such as route guidance, integrated traffic control and demand management. In this paper, a general DSS architecture is presented and its main components are analyzed and discussed. In particular, attention is focused on the model base, composed of the following relevant tools: resource optimization models, traffic simulation and evaluation models. The latter are based on cost-benefit effectiveness, multicriteria analysis and goal achievement analysis. Finally, some of the ideas and results attained by the research we are currently carrying out within Drive/EEC and Prometheus/Eureka projects are illustrated.

The air traffic flow control problem as an application of network theory

Abstract In this paper the air traffic flow control is approached as a constrained optimization problem on a multicommodity network. The proposed dynamic mathematical model, by means of a suitable time discretization, has been changed into a “static” one, in order to use static network flow algorithms while taking into account the “unsteady” nature of the air traffic congestion problems. The complexity of the model requires some preliminary effort, such as the identification of some characteristic parameters of the system. In this paper, the network theory is applied to evaluate the influence of the time discretization interval on the model significancy with respect to the actual traffic situation. In particular, a computational example concerning the Rome air traffic control region is presented and the relative results are discussed.

New operations research and artificial intelligence approaches to traffic engineering problems

Abstract The purpose of this paper is to review some of the main Operations Research (OR) and Artificial Intelligence (AI) research achievements in the field of traffic engineering, with particular reference to road traffic control. Therefore, the performances of the discussed approaches are illustrated and compared with respect to the features and the requirements which characterize some of the most relevant problems in the area of interest. The potential for a combined use of typical OR and AI methods and techniques when solving complex real-world, large-size traffic control problems is also emphasized. Finally, some concluding remarks are drawn that highlight the new challenges awaiting for the scientific community efforts.

TRANSPORT AND ENVIRONMENT INTERACTIONS: THE ITALIAN FRAMEWORK

Abstract With road traffic in Europe forecast to increase, strategies are needed to keep transportation sector growth within the bounds imposed by a sustainable development. Research is contributing through a large number of projects dealing with transport–environment interactions. This paper reviews international research activities in this field, focusing on technological innovations, air and noise pollution prediction models, and existing tools for socioeconomic evaluation of traffic impacts on the environment. In particular, research projects of the Second Special Project on Transport (PFT2) of the Italian National Research Council (CNR) are outlined.

Multicriteria Evaluation Model of Public Transport Networks

This paper focuses on the use of multicriteria methods as a tool for adequate decision making in urban transportation management aiming at reorganising bus transit system. In particular, it presents the main problems faced in the topic of multicriteria evaluation models, taking into account the different objectives and impacts, considering, appropriate performance indicators related to environment, safety, efficiency, quality, etc. This analysis has been performed on the urban network of Parma, a medium size Italian city, assuming as reference situation the existing public transit network and proposing three alternative networks.