Now showing items 11-15 of 15
perm mateda: A matlab toolbox of estimation of distribution algorithms for permutation-based combinatorial optimization problems
Permutation problems are combinatorial optimization problems whose solutions are naturally codified as permutations. Due to their complexity, motivated principally by the factorial cardinality of the search space of ...
Multi-objectivising Combinatorial Optimisation Problems by means of Elementary Landscape Decompositions
In the last decade, many works in combinatorial optimisation have shown that, due to the advances in multi-objective optimisation, the algorithms from this field could be used for solving single-objective problems as well. ...
Early classification of time series by simultaneously optimizing the accuracy and earliness
The problem of early classi cation of time series appears naturally in contexts where the data, of temporal nature, is collected over time, and early class predictions are interesting or even required. The objective is to ...
Estimating attraction basin sizes
The performance of local search algorithms is influenced by the properties that the neighborhood imposes on the search space. Among these properties, the number of local optima has been traditionally considered as a ...
A note on the Boltzmann distribution and the linear ordering problem
The Boltzmann distribution plays a key role in the field of optimization as it directly connects this field with that of probability. Basically, given a function to optimize, the Boltzmann distribution associated to this ...