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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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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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A Primer on Memetic Algorithms
2012Memetic Algorithms (MAs) are population-based metaheuristics composed of an evolutionary framework and a set of local search algorithms which are activated within the generation cycle of the external framework, see [376]. The earliest MA implementation has been given in [621] in the context of the Travelling Salesman Problem (TSP) while an early ...
Neri, Ferrante, Cotta, Carlos
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Memetic Algorithms for Nurse Rostering
2005Nurse rostering problems represent a subclass of scheduling problems that are hard to solve. The goal is finding high quality shift and resource assignments, satisfying the needs and requirements of employees as well as the employers in healthcare institutions. In this paper, a real case of a nurse rostering problem is introduced.
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Improved Memetic Programming algorithm
International Journal of Operational Research, 2021Souhir Elleuch, Bassem Jarboui
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Shuffled frog-leaping algorithm: a memetic meta-heuristic for discrete optimization
Engineering Optimization, 2006Kevin Lansey
exaly