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- Olivia Rossi-Doria, Michael Sampels, +9 authors Thomas Stützle
- PATAT
- 2002

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 Algorithms, Ant Colony Optimization, Iterated Local Search, Simulated Annealing, and Tabu… (More)

- Marco Chiarandini, Mauro Birattari, Krzysztof Socha, Olivia Rossi-Doria
- J. Scheduling
- 2006

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)

In this article, we study Pareto local optimum sets for the biobjective Traveling Salesman Problem applying straightforward extensions of local search algorithms for the single objective case. The performance of the local search algorithms is illustrated by experimental results obtained for well known benchmark instances and comparisons to methods from… (More)

- Leonora Bianchi, Mauro Birattari, +5 authors Tommaso Schiavinotto
- J. Math. Model. Algorithms
- 2006

This article analyzes the performance of metaheuristics on the vehicle routing problem with stochastic demands (VRPSD). The problem is known to have a computational demanding objective function, which could turn to be infeasible when large instances are considered. Fast approximations of the objective function are therefore appealing because they would… (More)

- Anders Helmar, Marco Chiarandini
- 2011

A coloring of an undirected graph is a labelling of the vertices in the graph such that no two adjacent vertices receive the same label. The sum coloring problem asks to find a coloring, using natural numbers as labels, such that the total sum of the colors used is minimized. We design and test a local search algorithm, based on variable neighborhood search… (More)

Graph coloring is a well known problem from graph theory that, when solving it with local search algorithms, is typically treated as a series of constraint satisfaction problems: for a given number of colors k, one has to find a feasible coloring; once such a coloring is found, the number of colors is decreased and the local search starts again. In this… (More)

The goal of this report is to give an analysis of the run time distributions for the algorithms considered in the experimental evaluation of the Course Timetabling problem [8]. Furthermore we investigate the hardness of the instances produced by the random instance generator proposed by Rossi-Doria and Ben Paechter [8]. This analysis confirms the… (More)

- Marco Chiarandini, Thomas Stützle
- Constraints
- 2007

The graph set T-colouring problem (GSTCP) generalises the classical graph colouring problem; it asks for the assignment of sets of integers to the vertices of a graph such that constraints on the separation of any two numbers assigned to a single vertex or to adjacent vertices are satisfied and some objective function is optimised. Among the objective… (More)

We give a short description of the solver that ranked third in Track Two of the International Timetabling Competition 2007 (ITC2007). It implements a heuristic approach based on stochastic local search and consists of several modules that were found to be useful in different phases of the solution process. Common to all modules is the consideration of only… (More)

- Leonora Bianchi, Mauro Birattari, +5 authors Tommaso Schiavinotto
- 2004

X. Yao et al (Eds.): PPSN VIII, LNCS 3242, pp. 450–460, 2004. c © Springer-Verlag Berlin Heidelberg 2004 Abstract. 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… (More)