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Distance-based exponential probability models on constrained combinatorial optimization problems
Estimation of distribution algorithms have already demonstrated their utility when solving a broad range of combinatorial problems. However, there is still room for methodological improvements when approaching constrained ...
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. ...
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 ...