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Titlebook: Algorithm Engineering; Selected Results and Lasse Kliemann,Peter Sanders Book 2016 Springer International Publishing AG 2016 computational

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發(fā)表于 2025-3-21 16:10:07 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
期刊全稱Algorithm Engineering
期刊簡(jiǎn)稱Selected Results and
影響因子2023Lasse Kliemann,Peter Sanders
視頻videohttp://file.papertrans.cn/153/152822/152822.mp4
發(fā)行地址Written by experts.High quality selected papers.Unique visibility.Includes supplementary material:
學(xué)科分類Lecture Notes in Computer Science
圖書封面Titlebook: Algorithm Engineering; Selected Results and Lasse Kliemann,Peter Sanders Book 2016 Springer International Publishing AG 2016 computational
影響因子.Algorithm Engineering is a methodology for algorithmic research that combines theory with implementation and experimentation in order to obtain better algorithms with high practical impact. Traditionally, the study of algorithms was dominated by mathematical (worst-case) analysis. In Algorithm Engineering, algorithms are also implemented and experiments conducted in a systematic way, sometimes resembling the experimentation processes known from fields such as biology, chemistry, or physics. This helps in counteracting an otherwise growing gap between theory and practice..
Pindex Book 2016
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書目名稱Algorithm Engineering影響因子(影響力)




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書目名稱Algorithm Engineering網(wǎng)絡(luò)公開度學(xué)科排名




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Route Planning in Transportation Networks,zed instances requires simplifications or heavy preprocessing. The multimodal route planning problem, which seeks journeys combining schedule-based transportation?(buses, trains) with unrestricted modes?(walking, driving), is even harder, relying on approximate solutions even for metropolitan inputs.
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Algorithm Engineering in Robust Optimization,nt of algorithms, some papers deal with the evaluation of a particular concept in case studies, and work on comparison of concepts just starts. What is still a drawback in many papers on robustness is the missing link to include the results of the experiments again in the design.
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Book 2016r algorithms with high practical impact. Traditionally, the study of algorithms was dominated by mathematical (worst-case) analysis. In Algorithm Engineering, algorithms are also implemented and experiments conducted in a systematic way, sometimes resembling the experimentation processes known from
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Roberta Pace,Roberto Ham-Chandee applications of computing low-discrepancy point sets, low-congestion routing, the max-coverage problem in hypergraphs, and broadcast scheduling. While mostly surveying results of the last 5 years, we also give a simple, unified proof for the correctness of the different dependent randomized rounding approaches.
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