Falkenauer, E, Genetic Algorithms and Grouping Problems, Wiley, 1998.Genetic Algorithms and Grouping Problems - Falkenauer - 1998Falkenauer, E. (1998) Genetic Algorithms and Grouping Problems. John Wiley and Son Ltd, New YorkFALKENAUE E.Genetic algorithms and grouping problems.. 1998...
Genetic algorithms (GAs) are search methods based on principles of natural selection and genetics (Fraser, 1957;Bremermann, 1958;Holland, 1975). We start with a brief introduction to simple genetic algorithms and associated terminology. to check access. References Asoh, H. and Mühlenbein, H., ...
Battaglia, Genetic algorithmsand clustering: An application to Fisher’s iris data, in S.Borra, R. Rocci, M. Vichi, & M. Schader (Eds.), Advances inclassification and data analysis (New York: Springer-Verlag,2001), 109–118. [13] S. Paterlini, S. Favaro, & T. Minerva, Genetic appr...
That is, the linguistics people are looking at patterns in language, and that's what bioinformatics people do--looking for patterns within sequences of DNA or protein. Creation of databases Development of algorithms and statistics Analysis of data and interpretation Track 15: Reproductive Genetics/Pr...
The Balancing of Mixed-Model Hybrid Assembly Lines with Genetic AlgorithmsBook © 2006 Overview Authors: Brahim Rekiek , Alain Delchambre Presents techniques based on the Grouping Genetic Algorithm which can be used to aid efficient assembly line design Includes supplementary material: sn.pub/...
A hybrid grouping genetic algorithm for the inventory routing problem with multi-tours of the vehicleMeta-heuristic and heuristics algorithmsIn this paper we analyse the inventory routing model as described recently by Aghezaff et al. in which the work of each vehicle can be organized in multi-...
Among these metaheuristics, Genetic Algorithms (GA) are very popular (Goldberg, 1989). GAs explore the search space by using the Darwinian principles of natural selection. Due to their success in solving a wide variety of problems, several researchers have applied GA on GPP. However, only a ...
In this paper, we introduce Genetic State-Grouping Algorithm (GSGA) enhanced by deep reinforcement learning. It is an integration of genetic algorithms and State Grouping, our genuine method, in pursuit of increasing deep reinforcement learning’s learning effectiveness in terms of time and resource...
Wang J, Zhou Y, Wang Y, Zhang J, Chen CLP, Zheng Z (2016) Multiobjective vehicle routing problems with simultaneous delivery and pickup and time windows: Formulation, instances, and algorithms. IEEE Transact Cybernet 46(3):582–594. https://doi.org/10.1109/TCYB.2015.2409837 Article MATH Go...
In this paper, we proposed an efficient genetic algorithm that will be applied to linear programming problems in order to find out the Fittest Chromosomes. This paper aim to find the optimal strategy of game theory in basketball by using genetic algorithms and linear programming as well as the ...