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OR@DII - Operational Research at Department of Information Engineering

Simple Ideas Are Often The Best                                                                                                                                        University of Brescia


Operational Research Group
Dip. di Ingegneria dell'Informazione
via Branze, 38
(25123) Brescia

+39 030 371 5448
+39 030 371 5935

Since 2007, OR@DII is the Operational Reserch group working at the Department of Information Engineering (DII) of the University of Brescia. Its research activity is focused on the development of optimization models and algorithms. OR@DII is part of OR@BRESCIA, the interdepartmental Operational Research group of the University of Brescia.

Vehicle Routing Problems


Optimizing profits, control costs and improving operational efficiencies in static and dynamic routing problems subject to real-life constraints such as time window restrictions, heterogeneous vehicle fleet, orders with multiple pick-up and delivery locations, split deliveries, and so on.

  • Time Dependent Traveling Purchaser Problem
  • The Dynamic Traveling Purchaser Problem with Stochastic Quantities
  • Distance Constrained Multiple Vehicle Traveling Purchaser Problem
  • Team Orienteering Problem with Time Windows
  • Supplier selection problem with quantity discounts and truckload shipping
  • Dynamic traveling purchaser problem
  • Dynamic Multi-Period Routing Problem
  • Dynamic traveling purchaser problem
  • Traveling Purchaser Problem with Budget Constraint
  • Bounded Version of the Uncapacitated TPP
  • Real-time vehicle routing
  • Skip delivery problem
  • Vehicle Routing Problem with Time Windows and Simultaneous Pick-up and Delivery

>> See our publications on this topic

Arc Routing Problems


Models and algotithms to solve classical or new problems in the Arc Routing field. These problems find various applications such as street sweeping, snow plowing, garbage collection, mail delivery, school bus routing, meter reading, and so on.

  • Directed Profitable Rural Postman Problem;
  • Undirected Capacitated Arc Routing Problem with Profits.

>> See our publications on this topic

Supplier Selection / Procurement Logistics Problems


Models and algorithms for procurement problems in which a buyer has to purchase goods form suppliers.

  • Shipper's Lane Selection Problem;
  • Capacitated Total Quantity Discount Problem;
  • Capacitated Traveling Purchaser Problem - Total Quantity Discount;
  • Capacitated Traveling Purchaser Problem;
  • Stochastic Traveling Purchaser Problem;
  • Multi-vehicle Traveling Purchaser Problem;
  • Multi-vehicle Traveling Purchaser Problem - Exclusionary Side Constraints.

>> See our publications on this topic

Finance Problems


Models and algorithms for portfolio selection problems with real features (transaction costs, minimum transaction lots, threshold on investment). Risk management based on the most recent achievements in portfolio theory and risk measures. Scenarios generation techniques.

  • Conditional value at risk;
  • Portfolio selection with transaction costs and rounds;
  • Portfolio rebalancing;
  • single-period portfolio optimization;
  • Two-Period Portfolio Selection Model for Asset-backed Securitization;
  • Mutual funds portfolio selection;
  • Lease Contracts in an Asset Backed Securitization;
  • Portfolio Selection Problem with Minimum Transaction Lots.

>> See our publications on this topic

Scheduling Problems


Models and algorithms to solve job/task scheduling ploblems.

  • Scheduling operations and personnel for surgical operating rooms
  • Scheduling groups of tasks with precedence constraints;

>> See our publications on this topic

Combinatorial Optimization Problems


Models and algorithms to solve classical (and variants of) combinatorial optimization ploblems, such as the TSP, bin packing problem, knapsack 0-1, matching problems, and so on.

  • Multidimensional Knapsack Problem;
  • Subset-sum Problem;
  • Scheduling groups of tasks with precedence constraints;
  • Generalized Independent Set Problem.

>> See our publications on this topic