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A Heuristic for Optimization of Metaheuristics by Means of Statistical Methods
(Scitepress, 2017-01-01)
The fine-tuning of the algorithms parameters, specially, in metaheuristics, is not always trivial and often is performed by ad hoc methods according to the problem under analysis. Usually, incorrect settings influence both ...
A statistical approach for the fine-tuning of metaheuristics: A case study combining design of experiments and racing algorithms
(2015-01-01)
The fine-tuning of heuristics and metaheuristics exercises a great influence in both the solution process, as well as in the quality of results of optimization problems. The search for the best fit of these algorithms is ...
Genetic algorithm, MIP and improvement heuristic applied to the MLCLP with backlogging
(2013-08-21)
The present paper solves the multi-level capacitated lot sizing problem with backlogging (MLCLSPB) combining a genetic algorithm with the solution of mixed-integer programming models and the improvement heuristic fix and ...
Quaternionic flower pollination algorithm
(2017-01-01)
Metaheuristic-based optimization techniques offer an elegant and easy-to-follow framework to optimize different types of problems, ranging from aerodynamics to machine learning. Though such techniques are suitable for ...
GRASP algorithm for charging coordination of plug-in electric vehicles in electrical distribution systems
(2017-01-04)
A new methodology based on the GRASP (Greedy Random Adaptative Search Procedure) metaheuristic is proposed in this paper in order to solve the plug-in electric vehicle (PEV) charging coordination problem in electrical ...
GRASP Algorithm for Charging Coordination of Plug-In Electric Vehicles in Electrical Distribution Systems
(Ieee, 2016-01-01)
A new methodology, based on the GRASP (Greedy Random Adaptative Search Procedure) metaheuristic is proposed in this paper in order to solve the plug-in electric vehicle (PEV) charging coordination problem in electrical ...
Co-reference Analysis Through Descriptor Combination
(Springer, 2018-01-01)
NELL (Never-Ending Language Learning) is the first never-ending learning system presented in the literature. It has been modeled to create a knowledge based on an autonomous way, reading the web 24 hours per day, 7 days ...
Network reconfiguration of distribution systems using metaheuristics and reliability measures
(2009-12-09)
In an evermore competitive environment, power distribution companies need to continuously monitor and improve the reliability indices of their systems. The network reconfiguration (NR) of a distribution system is a technique ...
Fine-Tuning Infinity Restricted Boltzmann Machines
(Ieee, 2017-01-01)
Restricted Boltzmann Machines (RBMs) have received special attention in the last decade due to their outstanding results in number of applications, such as face and human motion recognition, and collaborative filtering, ...
Enhancing brain storm optimization through optimum-path forest
(2018-08-20)
Among the many interesting meta-heuristic optimization algorithms, one can find those inspired by both the swarm and social behavior of human beings. The Brain Storm Optimization (BSO) is motivated by the brainstorming ...