会议信息

ALENEX 2027: SIAM Symposium on Algorithm Engineering and Experiments

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截稿日期:
2026-07-20 已截稿
通知日期:
会议日期:
2027-01-24
会议地点:
Philadelphia, Pennsylvania, USA
届数:
ICORE: A   QUALIS: B1   浏览: 37604   关注: 7   参加: 0
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ALENEX
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会伴指数 (CP-I)

76.3 / 100
全站第 248 名 / 共 5,759 个会议 · 前 5%

理论与算法 第 17 / 142

学术认可 (35%)
88
投稿选择性 (20%)
66
会议传承 (20%)
81
社区关注 (10%)
33
资料公开度 (15%)
85

用到的输入: 收录等级：ICORE A, QUALIS B1 · 录用率：40.1%（有记录的 5 届的均值） · 有据可查的届次：19 · 在会伴关注它的研究者：7 人 · 过去 24 个月打开过本页的研究者：5 人

公开资料里还缺: 最佳论文记录 (+2.3)
主办方认领本会议后，可直接在这一页补上；分数每晚重算。如何提升这个分数

置信度 100% —— 分数中有多大比例来自实际观测到的数据，而不是中性基准。 这个分数是怎么算出来的 · 查看完整榜单 · 算法版本 1.2 · 算于 2026-10-25

征稿

ALENEX 2027 (SIAM Symposium on Algorithm Engineering and Experiments) is a ICORE A / QUALIS B1 conference held in Philadelphia, Pennsylvania, USA on 2027-01-24. The paper submission deadline is 2026-07-20.

The aim of ALENEX is to provide a forum for the presentation of original research in the design, implementation, and experimental evaluation of algorithms and data structures. Typical submissions will include an extensive experimental analysis of nontrivial algorithmic results, ideally bridging the gap between theory and practice. We also invite submissions that address methodological issues and standards in the experimental evaluation of algorithms and data structures. We welcome submissions on a broad range of topics within algorithm engineering and the experimental analysis of algorithms and data structures, including but not limited to the following: Combinatorial optimization and mathematical programming, including scheduling and resource allocation problems Computational biology and bioinformatics Data science and data management, including databases Design and analysis of application-inspired exact, approximation, randomized, streaming, and learning-augmented algorithms Graph and hypergraph algorithms, including problems arising in network science and complex networks String algorithms and data structures Computational geometry Interaction between algorithms and modern computing platforms, including challenges arising from memory hierarchies, accelerators, and novel memory technologies Parallel and distributed computing, including algorithms, architectures, distributed systems, and all parallelism ranging from instruction-level and multi-core all the way to clouds and Exascale computing Machine learning and statistical methods for solving combinatorial problems Other applications arising from security, computational finance, computational chemistry/physics, quantum computing, etc.
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录用率

平均录用率: 32.9% 14 年间 (2007–2022).

年份提交数录用数录用率(%)
2022391743.6%
2020471736.2%
2019461737%
2018441943.2%
2017522140.4%
2016381539.5%
2015541527.8%
2014681522.1%
2013471531.9%
2012491530.6%
2011471531.9%
2010531528.3%
2009641523.4%
2007601525%

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CKnowledge-Based Systems7.2Elsevier0950-7051
BSoftware & Systems Modeling3.2Springer1619-1366
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CFuture Generation Computer Systems5.9Elsevier0167-739X
CNeurocomputing6.5Elsevier0925-2312
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