Pasquale Carotenuto

Finding minimum and equitable risk routes for hazmat shipments

This paper deals with the generation of minimal risk paths for the road transportation of hazardous materials between an origin–destination pair of a given regional area. The main considered issue is the selection of paths that minimize the total risk of hazmat shipments while spreading the risk induced on the population in an equitable way. The problem is mathematically formulated, and two heuristic algorithms are proposed for its solution. Substantially, these procedures are modified versions of Yens algorithm for the k-shortest path problem, which take into due consideration the risk propagation resulting from close paths and spread the risk equitably among zones of the geographical region in which the transportation network is embedded. Furthermore, a lower bound based on a Lagrangean relaxation of the given mathematical formulation is also provided. Finally, a series of computational tests, referring to a regional area is reported.

A tabu search approach for scheduling hazmat shipments

Vehicle routing and scheduling are two main issues in the hazardous material (hazmat) transportation problem. In this paper, we study the problem of managing a set of hazmat transportation requests in terms of hazmat shipment route selection and actual departure time definition. For each hazmat shipment, a set of minimum and equitable risk alternative routes from origin to destination points and a preferred departure time are given. The aim is to assign a route to each hazmat shipment and schedule these shipments on the assigned routes in order to minimize the total shipment delay, while equitably spreading the risk spatially and preventing the risk induced by vehicles traveling too close to each other. We model this hazmat shipment scheduling problem as a job-shop scheduling problem with alternative routes. No-wait constraints arise in the scheduling model as well, since, supposing that no safe area is available, when a hazmat vehicle starts traveling from the given origin it cannot stop until it arrives at the given destination. A tabu search algorithm is proposed for the problem, which is experimentally evaluated on a set of realistic test problems over a regional area, evaluating the provided solutions also with respect to the total route risk and length.

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.

Hybrid genetic algorithm to approach the DARP in a demand responsive passenger service

Abstract In this work, we address a Demand Responsive Transport System capable of managing incoming transport demand using a solution architecture based on a two- stage algorithm to solve a Dial-a-Ride Problem instance. In the first stage, a constructive heuristic algorithm quickly provides a feasible solution to accept the incoming demand. The algorithm in the second stage is a specialized Hybrid Genetic Algorithm that attempts to improve the solution evaluated at the first stage by using the time between two consecutive transportation events.

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.

A Decentralized Performance Measurement System for Supply Chain

The growth of the networking possibilities allows extending the monitoring and evaluation processes beyond the walls of a single company to verify the coherence with the global strategy of a supply chain nevertheless diminishing the local control. In this paper we start from the development of the overall architecture of a performance measurement system which reflects the structure of the supply chain under consideration. A preliminary multi-agents model is then discussed enhancing the benefits of such a structure in comparison with traditional systems.

A Multi-depot Periodic Vehicle Routing Model for Petrol Station Replenishment

The petrol station replenishment problem consists in delivering fuel oils from a set of storage depots to a set of petrol stations during a few days planning horizon. This problem is addressed by an oil company which, for example, has to decide simultaneously the weekly fuel oil replenishment plan for each station, and, for each day of the week, the tank truck (vehicle) routes from depots to stations, in order to deliver the planned fuel oil replenishment amounts to petrol stations. Assuming a fleet of homogeneous tank trucks, the aim is to minimize the total distance travelled by tank trucks during the week, while loading tank trucks possibly near to their capacity in order to maximize the resource utilization. We model the problem as a generalization of the Multi-Depot Periodic Vehicle Routing Problem (MDPVRP) and provide a mathematical formulation. Due to the large size of the real instances which the company has to deal with, we solve the problem heuristically. We propose a hybrid genetic algorithm that successfully address the problem. The algorithm is derived from a known hybrid genetic algorithm for the MDPVRP, and adopts additional techniques and features tailored for the particular fuel oil distribution problem. It is specifically designed to deal with real instances derived from the fuel oil distribution in the European context that are profoundly different from the MDPVRP instances available from the literature. The proposed algorithm is evaluated on a set of real case studies and on a set of randomly generated instances that hold the same characteristics of the former.

A Metaheuristic Approach for Hazardous Materials Transportation

The transportation of hazardous materials is a growing problem due to the increasing transported volumes. What differentiates hazardous material shipments from shipments of other materials is the risk associated with an accidental release of hazardous materials during transportation. A possible solution to reduce the occurrence of dangerous events is to provide travel plans that establish a fair spatial and temporal distribution of the risk. The objective of this work is to study the problem of routing and scheduling a set of hazardous materials shipments, minimizing the travel total risk while spreading the risk among different zones of the geographical region where the transportation network is defined. We propose a genetic algorithm that, given a set of dissimilar routes for every origin-destination pair, selects a route and defines a departure time for every shipment with the aim of minimizing the total risk of the travel plans. The genetic algorithm is experimentally evaluated on a set of realistic scenarios defined on a regional area.

Advanced Research on Transport-Environment Interactions

Abstract Since road traffic in Europe is forecast to increase in the future, articulated strategies are needed in order to keep transportation sector growth within the bounds imposed by a sustainable development. Scientific research is contributing to pursue this aim through a large number of projects dealing with transportation-environment interactions. This paper reviews international research activities in this field, focusing particularly on technological innovations, air and noise pollution prediction models as well as on existing tools for socio-economic evaluation of traffic impacts on the environment. In particular, research projects of the Second Special Project on Transportation (PFT2) of the Italian National Research Council (CNR) are outlined. The aim of this paper is to underline the most relevant research topics on which it is necessary to concentrate the efforts if it is expected the community welfare to be achieved.

A Collaborative Decisional System to Support a Business Model for the Development of Charging Infrastructure

The obstacles to the E-Mobility (EM)’s development are widely discussed both in scientific and in industrial fields. Approaches to overcome these obstacles are still not consolidate. At the same time, it is not so clear, what Business Models (BM) are more sustainable for the owners of Charging Infrastructure (CI). With the aim to support the development of charging network (CN), the authors propose a new BM based on intelligent, collaborative and digital services for all actors of the value chain. The implementation of this BM starts with the development of a decisional structure (DS) and the sharing of data and information among all operators that are involved into the charging process. The main elements of the model are explained and the first results of implementation are given. Future development are discussed to enrich the research and to supply at industrial field a useful tool to face decisions in the real context of CNs.