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Titlebook: Bioinspired Heuristics for Optimization; El-Ghazali Talbi,Amir Nakib Book 2019 Springer Nature Switzerland AG 2019 Bioinspired Heuristics.

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期刊全称Bioinspired Heuristics for Optimization
影响因子2023El-Ghazali Talbi,Amir Nakib
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发行地址Presents recent research on bioinspired heuristics.Provides a comprehensive background to bioinspired heuristics for optimization.Highlights state-of-the-art developments in bioinspired heuristics res
学科分类Studies in Computational Intelligence
图书封面Titlebook: Bioinspired Heuristics for Optimization;  El-Ghazali Talbi,Amir Nakib Book 2019 Springer Nature Switzerland AG 2019 Bioinspired Heuristics.
影响因子This book presents recent research on bioinspired heuristics for optimization. Learning- based and black-box optimization exhibit some properties of intrinsic parallelization, and can be used for various optimizations problems. Featuring the most relevant work presented at the 6th International Conference on Metaheuristics and Nature Inspired Computing, held at Marrakech (Morocco) from 27th to 31st October 2016, the book presents solutions, methods, algorithms, case studies, and software. It is a valuable resource for research academics and industrial practitioners.. .
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Intrusion Detection System Based on a Behavioral Approach,chine) to develop a model for IDS. The simulation results show a significant amelioration in performances, all tests were realized with the NSL-KDD data set. In comparison with other methods based on the same dataset, the proposed model shows a high detection performance.
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Multi-capacitated Location Problem: A New Resolution Method Combining Exact and Heuristic Approachean problems available in literature. The NFF method provides very good results for low and medium difficulty instances, but it is less effective for the more complex ones. To remedy this problem, the method will be supplemented by column generation approach.
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Adapted Bin-Packing Algorithm for the Yard Optimization Problem,solve it. Computational results are presented at the end using instances created and adapted to the ones existing in the literature. Our results illustrate the performance of the applied method for the medium and big instances.
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Epidemiology of Renal Cell Carcinoma mono-objective and multi-objective cases. Secondly, we suggest an extension of two well-known Pareto-base evolutionary algorithms namely, SPEA2 and NSGAII. Finally, the extended algorithms are applied to solve a multi-objective Vehicle Routing Problem (VRP) with uncertain demands.
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Molecular Genetics of Kidney Cancerigated, and solutions are obtained through the use of heuristics and a commercial optimization package. The computational experiments (based in real cases) showed that the method is more efficient in producing a feasible solution than the solver.
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