Cryopreservation with storage at very low temperatures is essential to make full use of this technology for both biological and commercial reasons. However, most mammalian cells will die if exposedâ€¦ (More)

The network reconfiguration for service restoration in distribution systems is a combinatorial complex optimization problem that usually involves multiple non-linear constraints and objectivesâ€¦ (More)

Linkage Learning (LL) was proposed as a methodology to enable Genetic Algorithms (GAs) to solve complex optimization problems more effectively. Its main idea relies on a reductionist assumption,â€¦ (More)

In general, Multi-objective Evolutionary Algorithms do not guarantee find solutions in the Pareto-optimal set. We propose a new approach for solving decomposable deceptive multi-objective problemsâ€¦ (More)

Linkage Learning (LL) is an important issue concerning the development of more effective genetic algorithms (GA). It is from the identification of strongly dependent variables that crossover can beâ€¦ (More)

Model-based Genetic Algorithms (GAs), as the Linkage Tree Genetic Algorithm (LTGA) and most Estimation of Distribution Algorithms (EDAs), assume a reductionist perspective when solving optimizationâ€¦ (More)

In this report we briefly discuss about two aspects related to the understanding of complex networksâ€™ structure and dynamics. First of all, is shown how we can use an Information theory approach toâ€¦ (More)

We describe a compact method to transform arc routing problem instances into node routing problem instances. Any node routing problem instance thus created must be solved by a branch-and-priceâ€¦ (More)