Results 201 to 210 of about 15,134 (244)
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Bioinspired Multi-memetic Algorithm
2021The paper considers a multi-memetic ant algorithm of discrete optimization. An algorithm has been developed for choosing and appropriate strategies for using a meme from a swarm of available memes. The work of multi-memetic ant algorithm of discrete optimization is illustrated by the example of a partition problem, which is widely used in solving ...
Boris K. Lebedev +2 more
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A differential memetic algorithm
Artificial Intelligence Review, 2012Memetic algorithms have been devised to rectify the absence of a local search mechanism in evolutionary algorithms. This paper proposes a differential memetic algorithm (DMA). To this end, first we propose a differential bidirectional random search as a local search algorithm.
M. T. Vakil-Baghmisheh +1 more
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1994
A formal, representation-independent form of a memetic algorithm—a genetic algorithm incorporating local search—is introduced. A generalised form of N-point crossover is defined together with representation-independentpatching and hill-climbing operators.
Nicholas J. Radcliffe, Patrick D. Surry
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A formal, representation-independent form of a memetic algorithm—a genetic algorithm incorporating local search—is introduced. A generalised form of N-point crossover is defined together with representation-independentpatching and hill-climbing operators.
Nicholas J. Radcliffe, Patrick D. Surry
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Memetic Algorithms and Memetic Computing Optimization: A Literature Review
Swarm and Evolutionary Computation, 2020Abstract Memetic computing is a subject in computer science which considers complex structures such as the combination of simple agents and memes, whose evolutionary interactions lead to intelligent complexes capable of problem-solving. The founding cornerstone of this subject has been the concept of memetic algorithms, that is a class of ...
Ferrante Neri, Carlos Cotta
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Multiobjective Memetic Algorithms
2012Multiple conflicting points of view, which are often taken into account in real life applications, naturally result in a multiple objective optimization problem (MOP) [848]. In order to find the best compromise solution of a MOP, or a good approximation of it, Multiobjective Optimization (MOO) methods need some preference information from a decision ...
Andrzej Jaszkiewicz +2 more
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2018
The remarkable flexibility of evolutionary computation (EC) in handling a wide range of problems, encompassing search, optimization, and machine learning, opens up a path to attaining artificial general intelligence. However, it is clear that excessive reliance on purely stochastic evolutionary processes, with no expert guidance or external knowledge ...
Abhishek Gupta, Yew-Soon Ong
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The remarkable flexibility of evolutionary computation (EC) in handling a wide range of problems, encompassing search, optimization, and machine learning, opens up a path to attaining artificial general intelligence. However, it is clear that excessive reliance on purely stochastic evolutionary processes, with no expert guidance or external knowledge ...
Abhishek Gupta, Yew-Soon Ong
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Memetic Algorithms in Bioinformatics
2012Bioinformatics is an exciting research field for memetic algorithms (MAs). Its core activity is the integration of techniques from Computer Science, Mathematics and Statistics to address challenging computational problems related with the analysis of large volumes of data.
Berretta, Regina +2 more
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Improving ontology alignment through memetic algorithms
2011 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2011), 2011Born primarily as means to model knowledge, ontologies have successfully been exploited to enable knowledge exchange among people, organizations and software agents. However, because of strong subjectivity of ontology modeling, a matching process is necessary in order to lead ontologies into mutual agreement and obtain the relative alignment, i.e., the
ACAMPORA, GIOVANNI +4 more
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MAPM: memetic algorithms with population management
Computers & Operations Research, 2006A new metaheuristic for (combinatorial) optimization is presented: memetic algorithms with population management or MA|PM. An MA|PM is a memetic algorithm, that combines local search and crossover operators, but its main distinguishing feature is the use of distance measures for population management.
Sörensen, Kenneth, Sevaux, Marc
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Improved Memetic Programming algorithm
International Journal of Operational Research, 2021Souhir Elleuch, Bassem Jarboui
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