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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)
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)
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)
In this article, we study local optima, in the Pareto sense, of the biobjective Travelling Salesman Problem by means of simple extensions of local improvement algorithms. We propose this approach as a first step for tackling a multiobjective problems that should be used as a reference for future comparisons with metaheuristics in multiobjective problems. We(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)
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)
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)