Raúl Baños

TL;DR: A review of the current state of the art in computational optimization methods applied to renewable and sustainable energy can be found in this article, which offers a clear vision of the latest research advances in this field.

TL;DR: MORPGEASA, a Pareto-based hybrid algorithm that combines evolutionary computation and simulated annealing, is proposed and analyzed for solving these multi-objective formulations of the VRPTW and the results obtained show the good performance of this hybrid approach.

TL;DR: Evaluated meta-heuristic techniques: genetic algorithms, simulated annealing, tabu search, and iterated local search were applied to a large irrigation water distribution network that has been proposed in a previous work to assess their performance in a practical application.

TL;DR: The procedure MT-PSA outperforms SPEA2 in the benchmarks here considered, with respect to the solution quality and execution time, and Computational results obtained on Solomon's benchmark problems show that the island-based parallelization produces Pareto-fronts of higher quality that those obtained by the sequential versions without increasing the computational cost.

TL;DR: This paper presents a new generational genetic algorithm (GGA+) that includes efficient initialisation methods and search operators under the guidance of modularity that enables a flexible and adaptive analysis of the characteristics of a network from different levels of detail according to an analyst’s needs.