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

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書目名稱Bioinspired Heuristics for Optimization影響因子(影響力)




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書目名稱Bioinspired Heuristics for Optimization被引頻次




書目名稱Bioinspired Heuristics for Optimization被引頻次學(xué)科排名




書目名稱Bioinspired Heuristics for Optimization年度引用




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書目名稱Bioinspired Heuristics for Optimization讀者反饋




書目名稱Bioinspired Heuristics for Optimization讀者反饋學(xué)科排名

雪白

Optimum

珊瑚

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.

英寸

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.

frozen-shoulder

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.

憤世嫉俗者

Mangle

SAGE

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.

放肆的你

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.