Chiara Bersani

Risk Averse Routing of Hazardous Materials with Scheduled Delays

The term “risk-averse” in the routing of hazardous material is used for problems whose objective is to find the best and safest routes to connect various origin-destination (OD) pairs, taking into account the objective of minimizing either the maximum risk or the maximum exposure. In recent works, it has been demonstrated that for repeated shipments, where the accident probabilities over the various links in the network are unknown, the safest strategy is generally based on the use of a multiple routes for each OD pair. In this work, it is shown that further improvements can be made through scheduling the deliveries, that is, spreading the risk both in space and in time. The scheduling is particularly relevant when the vulnerability of the network is time-dependent.

Economic and Risk Implications in the Distribution of Petrol Products to Service Stations under Retailer Managed and Vendor Managed Inventories

ABSTRACT Retailer inventory management is the common approach that is used by oil companies in the distribution of petrol products to service stations. Service station retailers send orders to the oil company vendor according to their own perception of inventory and of the future demand. The oil vendor consequently optimizes the deliveries by solving a related capacitated-vehicle routing problem. Nowadays, the technological possibility to monitor remotely the level of the underground storage tanks in the service stations allows a new formulation of the problem, planning deliveries based on the actual level of the inventory and on a prediction of future demand, that is, shifting also the inventory management on the vendor side. From a sustainable viewpoint, the centralization of the management of the retailer inventories has an economic impact, that in the case of petrol products is also related to risk impact, that has not yet been evaluated. Under this perspective, a comparison between the two approaches is described, where the vendor inventory management is proposed according to an original formulation of the problem integrating both the inventory and the routing costs in the objective function of the related mathematical programming formulation. This formulation has been implemented, tested and compared with respect to a simple simulated retailer inventory procedure in a series of random trials. In addition, the evaluation has been applied to an actual case study, related to the Nice (France) district, to evaluate the improvements of the performance of the distribution of petrol products by tank trucks when the central depot can receive the levels of the underground storage tanks in real-time. The results show that the proposed approach would have allowed a reduction in the number of deliveries and in the overall amount of kilometers necessary for the deliveries themselves, that is with a certain related economic impact. As a consequence, it is also shown that risk in the transportation of petrol products also decreases in the territory affected by this transportation, thus improving both the economic and the risk sustainability of this transport.

Accident occurrance evaluation in the pipeline transport of dangerous goods

A pipeline is a complex system, geographically spread on a wide territory, requiring technologies and methodologies to support the identification of pipeline segments that are highly potentially at risk of failure. This paper tackles a dual problem: to describe the most significant causes that may lead to a pipeline segment failure; to evaluate the occurrence of these causes leading to a failure, according to technical characteristics of the pipeline, infrastructures, territorial elements, and land use activities in the pipeline neighbourhood. This analysis constitutes the methodological basis to implement a Geographic Information System to support decisions as regards risk analysis and land planning criteria.

A Risk-Based System of Systems Approach to Control the Transport Flows of Dangerous Goods by Road

A risk-based approach to control dangerous goods (DG) transport flows by roads is proposed, solving a real-time flow assignment problem. The model takes into account the planned scheduling of the DG fleets. The objective is to readapt the schedule in real time, controlling the DG flow to minimize both the risk on the network and the gap between the proposed modified delivery and the planned one. The innovative aspect of the proposed approach is to balance the social objective of a national authority, thus minimizing the risk on the road infrastructures, with the economical objective of the DG distribution companies that have to minimize the actual time, as defined by the planned deliveries. The proposed DG transport model is defined according to a system of systems view. Each subsystem (SS) represents either a regional area or, more commonly, a segment of a road. The proposed approach provides a useful tool for evaluating the optimal speed for DG vehicles in each SS and the optimal amount of DG flow that should transit from one SS to another, following the planned delivery schedule. The problem has been tackled in two different formulations. First, a nonlinear mathematical programming formulation is defined. Then, according to simplifying assumptions, the problem is solved as a discrete-time finite horizon linear quadratic optimal control problem with a state feedback control. An exemplificative case study is used to show a comparison between the two formulations, as well as the effects of a risk sudden change in the overall DG routing.

A Distributed Information System Prototype to Detect and Monitor the Hazardous Material Transport on the Road in the Territory of Nice-Imperia-Ventimiglia

This paper presents a Decision Support System (DSS) for the detection and monitoring of Hazardous Material (hazmat) transportation on the road infrastructure Nice-Imperia-Savona between France and Italy that was developed in the TMD-NIS Interreg IIIA Alcotra Project. The final objective of the TMD-NIS project was to determine the most effective information and communication technologies and common operation strategies applicable in hazmat management in order to minimize the hazmat transport risk and to improve the road infrastructure safety conditions. An integrated and comparative assessment of the two alternative technologies was performed by the partners of the project: an image processing system to identify the ONU codes on the hazmat plates installed on each truck has been tested in France, while an on-board computer system to store and transmit information related to the hazmat physical conditions, vehicle’s locations and performance measures has been implemented in Italy. The collaboration between the different research institutions and the complementarities of the two specific approaches to define and monitor the hazmat vehicle flows allow comparison and validation of the acquired data related to the type, the amount and the itineraries of the hazmat vehicles which cover the trans-border road infrastructures daily. At present, the TMD-NIS project also provides a GIS utility that is available on the web to track in real-time hazmat vehicles that analyze data about hazmat flow and also to visualize the risk index for the highway from the toolbar barriers of St. Isidore (Nice) to the Ventimille.

Real-time risk definition in the transport of dangerous goods by road

The definition of risk in the transport of dangerous goods is an open issue. No international standard is currently defined. In addition, the definition of risk is directly related to the possibility to its control at decisional level, for example, by rerouting the traffic. In this work, a proposal to define risk at strategic, tactical, operational and realtime level is proposed. A system of systems vision of the definition at operational/realtime level is particularly promising of research aspects both from a SoSE and a technological viewpoint.

Bi-objective shortest path problem with one fuzzy cost function applied to dangerous goods transportation on a road network

The shortest path problem is a very well-known network problem, whose complexity sensibly increases from polynomial complexity to become a NP-hard problem when a multi-objective function is taken into account. In this work, an algorithmic approach to a bi-objective problem is described, where one objective has a fuzzy value, which makes even harder to get a solution. This kind of approach finds an applicative use in the case of dangerous goods transport by road, where a trade-off between the minimum cost and the minimum (or minmax) risk has to be solved in the delivery from a depot to petrol stations.

A multi-criteria methodology to evaluate the optimal location of a multifunctional railway portal on the railway network

The installation of a multifunctional railway portal (or TCCS – Train Conformity Check system) can contribute to improve the safety of a railway infrastructure. The TCCS can detect the conformity of the trains traveling along the tracks, and can transfer the status information to a main traffic control center. This paper proposes a methodological approach based on Analytic Hierarchy Process (AHP) to evaluate the optimal locations to install a TCCS on a railway section. The eligibility and ranking of the potential sites have been defined with respect to constraints related to the rail line track layout and geometry, the TCCS technological features, and the required safety distance allowing the train to stop. The proposed approach has been applied to a real case study on the Italian railway.

Optimal traffic flow assignment for planned deliveries in dangerous good transportation

In this paper, an approach to solve a flow assignment problem is proposed assuming known the whole trip planning of the fleets. The objective is to minimize both the risk of the network associated to the DG transport flow and the variance of the assigned delivery planning in respect to the expected one. Different simulation tests have been performed to evaluate the goodness of the proposed model, planning one or two deliveries from different OD pairs, varying risk values on the links of the network during the time horizon. The results demonstrates that model application guarantees a decrease of risk costs splitting flows on multiple paths avoiding to transit on links characterized by an high risk at a certain time, as well as the respect of expecting flow over each link.

Distributed Robust Control of the Power Flows in a Team of Cooperating Microgrids

This brief paper presents a mathematical formulation for a team of cooperating microgrids (TCM) proposing a robust distributed control strategy based on partially nested information. This brief paper faces one of the main problems in a TCM, which is to react to the unpredictable production/demand processes, optimizing power flows, and energy storage in each microgrid (MG). This brief paper focuses on a high-level control of the TCM through properly coordinating power that is exchanged among MGs. The robust distributed control strategy operates in order to minimize the maximum divergence both from an agreed power exchange among MGs and from a technical reference value of the energy storage system of each MG. The proposed approach is based on some quite recent results on robust control for cooperative teams. The robust control approach is tested through a case study.