Smart Industry: Operations research & Optimization

  • What it is

    Mobility experience with a research focus

  • Who it’s for

    PhD sandwich

Department

Department of Information Engineering (DINFO)

Main research activities/topics/projects

Hazmat transportation: Modern societies rely upon massive supplies of large amounts of commodities, some of which imply the use/production of hazardous materials (hazmat). A crucial step in the hazmat life cycle is transportation. An accident en route is a “low probability – high consequences” event and much effort has been devoted to the development of risk mitigation strategies. In this project, we are concerned with hazmat transportation by truck on a road network, where several alternative itineraries from origin to destination are worthy of choice. Two actors typically operate on the network with conflicting goals: carriers, interested in minimizing transportation costs, and local authorities, interested in reducing risk. More specifically, given (i) a set of origin-destination pairs and the hazmat quantities to be transported for each pair, (ii) the road network topology, and (iii) the cost and the risk of each arc, the aim is to reduce the total risk related to the hazmat itineraries, hopefully not to a sensitive detriment of cost. In a mixed urban setting, the shortest path is often a risky one. Whenever possible, the network administrator imposes on each driver a specific itinerary with lower risk. If not possible, the network administrator may enforce some restrictions regarding network usage, such as forbidding hazmat transit on some links or imposing tolls. Within this framework, we propose a new method that diverts vehicles from their shortest (and risky) path from origin to destination, by forcing each vehicle to pass through an intermediate checkpoint, a so-called gateway. Defining the optimal location of the gateways thus represents a challenging optimization problem and an interesting opportunity to mitigate risk.

Working language

English

Special entry requirements

Knowledge of (i) programming languages (C++ or Python), (ii) packages for formulating optimization models (Pyomo or similar), and (iii) Mixed Integer Linear Programming solvers (Gurobi or Cplex)

Duration in months (min-max)

PhD sandwich: 4-8

Contacts

Main scientific contact person

Paola Cappanera

+39 055 2758640

Write an e-mail

paola.cappanera