Olivia Rossi-Doria

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The main goal of this paper is to attempt an unbiased comparison of the performance of straightforward implementations of five different metaheuristics on a university course timetabling problem. In particular, the metaheuristics under consideration are Evolutionary Al-of all the algorithms use a common solution representation, and a common neighbourhood(More)
The university course timetabling problem is an optimisation problem in which a set of events has to be scheduled in timeslots and located in suitable rooms. Recently, a set of benchmark instances was introduced and used for an 'International Timetabling Competition' to which 24 algorithms were submitted by various research groups active in the field of(More)
The work presented in this thesis consists of two parts. The first part (Chapters 1 and 2) introduces a general formulation of Shop Scheduling problems, called the Group Shop Scheduling problem (GSP). This problem formulation covers among other Shop Scheduling problems the Job Shop Scheduling problem (JSP) and the Open Shop Scheduling problem (OSP). As(More)
This article analyses the performance of metaheuristics on the Vehicle Routing Problem with Stochastic Demands. The problem is known to have a computational demanding objective function, which could turn to be infeasible when large instances are considered. Therefore, fast approximations to the objective function would, at least, provide more time for(More)
ion refinement-based model checking has become a standard approach for efficiently verifying safety properties of hardware/software systems. Abstraction refinement algorithms can be guided by counterexamples generated from abstract transition systems or by fixpoints computed in abstract domains. Cousot, Ganty and Raskin recently put forward a new(More)
In the vehicle routing problem with stochastic demands a vehicle has to serve a set of customers whose exact demand is known only upon arrival at the customer's location. The objective is to find a permutation of the customers (an a priori tour) that minimizes the expected distance traveled by the vehicle. Since the objective function is computationally(More)
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