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A XOR-based ABC algorithm for solving set covering problems
(Springer Verlag, 2016)
FP-AK-QIEAR-R in protein folding application
(Institute of Electrical and Electronics Engineers Inc., 2017)
There are many Evolutionary Algorithms which main features are: population, evolutionary operations (crossover, mate, mutation and others). Most of them are based on randomness and follow a criteria using fitness like ...
General subpopulation framework and taming the conflict inside populations
(MIT PressCambridge, Mass, 2015)
Structured evolutionary algorithms have been investigated for some time. However,
they have been under explored especially in the field of multi-objective optimization.
Despite good results, the use of complex dynamics ...
Proposal and Comparative Study of Evolutionary Algorithms for Optimum Design of a Gear System
(Institute of Electrical and Electronics Engineers, 2019-12)
This paper proposes a novel metaheuristic framework using a Differential Evolution (DE) algorithm with the Non-dominated Sorting Genetic Algorithm-II (NSGA-II). Both algorithms are combined employing a collaborative strategy ...
Learning Fuzzy Cognitive Maps with modified asexual reproduction optimisation algorithm
(Elsevier B.V., 2019)
A survey of evolutionary algorithms for decision-tree induction
(IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INCPISCATAWAY, 2012)
This paper presents a survey of evolutionary algorithms that are designed for decision-tree induction. In this context, most of the paper focuses on approaches that evolve decision trees as an alternate heuristics to the ...
Three-phase harmonic distortion state estimation algorithm based on evolutionary strategies
(ELSEVIER SCIENCE SA, 2010)
This paper presents a new methodology to estimate unbalanced harmonic distortions in a power system, based on measurements of a limited number of given sites. The algorithm utilizes evolutionary strategies (ES), a development ...
A Probability-based Evolutionary Algorithm with Mutations to Learn Bayesian Networks
Bayesian networks are regarded as one of the essential tools to analyze causal relationship between events from data. To learn the structure of highly-reliable Bayesian networks from data as quickly as possible is one of ...
Recent metaheuristics for the Weighted Set Covering problem
(National Technical University of Athens, 2014)