In the Stacker Crane Problem (SCP), pairs of pickup and delivery points are designated on a graph, and a crane must visit these points to move objects from each pickup location to its respective delivery point. The goal is to minimize the total distance traveled. SCP is known to be NP-hard, even on tree structures. The only positive results, in terms of polynomial-time solvability, apply to graphs that are topologically equivalent to a path or a cycle. We propose an algorithm that is optimal for each fixed topology, running in near-linear time. This is achieved by demonstrating that the problem is fixed-parameter tractable (FPT) when parameterized by both the cycle rank and the number of branch vertices. This is joint work with Yike Chen and Ke Shi.

Speaker Bio

许超，电子科技大学计算机科学与工程学院副教授，博士生导师，算法与逻辑团队成员。许超主要从事组合优化和算法的基础研究，在SODA、Mathematical Programming、SICOMP，等组合优化和算法的国际顶级期刊/会议上发表多篇学术论文。现主持国家自然科学基金优秀青年（海外）项目。

Online Access

计算所环保园1号楼524会议室
腾讯会议号：605 5793 9921，密码：图灵机被提出的年份（4位）
B站直播网址：https://live.bilibili.com/22528138

请点击pdf查看详情。TFCS24-2 Slides – Bakh Khoussainov

Speaker Bio

Bakh Khoussainov，教授，新西兰院士，电子科技大学计算机学院全职教授（我国西部地区引进的第一位发达国家的院士），目前担任电子科技大学算法与逻辑团队主任。他长期从事理论计算机科学中计算与逻辑领域的研究工作，2005年被新西兰最顶尖权威的学术组织——新西兰皇家学会评选为新西兰皇家学会院士，被评价为“在逻辑与理论计算机科学领域的领先专家，工作涉及对可计算性和复杂性理论的深入和非常广泛的研究”。2019年获得德国洪堡研究奖，该奖项旨在授予在基础研究、理论创新、学科引领等方面上取得了卓越成就的研究者。同年他还获得伦敦数学学会与新西兰数学学会联合授予的唯一Aitken Lecturer称号，该荣誉称号每两年仅授予一名最具杰出贡献的新西兰数学家（截至目前仅有包括美国工业与应用数学学会会士（SIAM Fellow）Hinke Osinga教授在内的5位研究者获此殊荣）。2017年他因其对于奇偶博弈问题的突出贡献荣获CCF A类会议ACM STOC 2017年最佳论文奖。他还曾获得新西兰数学学会研究奖，此奖项为新西兰数学领域最高奖，每年仅颁发给一名新西兰数学家，该奖项还曾颁发给包括美国数学学会会士G. Martin, R. Downey教授（AMS Fellow）, M. Conder教授（AMS Fellow）等优秀数学家。

Host

Simons Institute for the Theory of Computing

Livestream

Calvin Lab Auditorium @ University of California, Berkeley

Online：Youtube

Score aggregation is the process of combining numerical scores or ratings from multiple sources or criteria into asingle aggregated score. It is widely used in decision-making scenarios where there are multiple factors or evaluators involved. Commonly used approaches for score aggregation include: weighted average, multi-criteria decision analysis, machine learning-based approaches, and so on. In this talk, we will give some nice algebraic and geometric explanations for score aggregation, and introduce a new aggregation model based on the spectral method.

Speaker Bio

肖鸣宇，中国计算机学会理事、理论计算机科学专委员会主任；电子科技大学计算机科学与工程学院教授，副院长，算法与逻辑实验室执行主任，国家级信息与网络安全虚拟仿真实验教学中心主任，国家级计算机实验教学示范中心主任。致力于算法、组合优化、机制设计、算法博弈论等方面的基础理论研究，在精确算法、参数算法、核心化算法等领域是国内外著名的专家，为电路满足问题（SAT）、最大独立集等多个基本NP难问题设计了当前最佳的精确算法和参数算法；并将算法理论应用于人工智能、工业优化、计算经济、运筹学等领域中取得了显著成效。近年来在算法理论、人工智能基础算法领域顶级期刊和会议上以单独作者和主要作者发表论文超过150篇，撰写英文专著1部，主持国家级项目10余项。

Host

Beijing Institute of Technology (BIT)

Online Meeting

北京友谊宾馆友谊宫第 8 号会议室

腾讯会议/ VooV Meeting： 409-540-830

经典的最小割问题是通过删除图中最少的顶点将图中两个终端顶点分割开来，这个问题的一个自然推广就是将图中多个终端顶点相互分割开来，这就是图多路分割问题(The MultiwayCut Problem)。尽管最小割问题存在快速的多项式算法，但是当需要分割3个或者更多终端顶点的时候，这个问题就变成了NP难的。对图多路分割问题来说，经典的最大流最小割这一对偶性质不存在了，找到一个比简单穷举搜素算法更快的算法也不容易。在无向图上，图多路分割问题目前最好的精确算法可以做到 $1.4767^n$时间，其中n是图中顶点的个数。在有向图上是否存在比简单穷举算法 $2^n$时间更快的算法却一直是一个未解决的公开难题。本文将介绍在有向图上如何在$1.9967^n$时间内解决图多路分割问题。

Speaker Bio

肖鸣宇，现为电子科技大学计算机科学与工程学院教授，副院长算法与逻辑实验室执行主任;中国计算机学会理事、理论计算机科学专业委员会主任;国家级信息与网络安全虚拟仿真实验教学中心主任国家级计算机实验教学示范中心主任。致力于算法、计算理论、图论与图算法、机制设计与算法博弈论等方面的基础理论研究，为SAT、最大独立集等多个基本NP难问题设计了当前最佳的精确算法和参数算法;并将算法理论应用于人工智能、工业优化、计算经济、运筹学等领域中取得了显著成效。近年来在算法理论、人工智能基础算法领域顶级期刊和会议上以单独作者和主要作者发表论文超过150篇，撰写英文专著1部。主持国家级科研项目10余项。

Host

Nankai University （南开大学）

Online Access

Online, Tencent Meeting: 547-454-448

Poster

Finitely presented algebraic systems, e.g, groups, are fundamental in algebra and computation, They have computably enumerable word equality problems and are finitely generated (f.g,), We refer to f.g, algebraic systems with computably enumerable word equality problems as computably enumerable. Not all computably enumerable, f.g algebraic systems are finitely presented.

This talk explores the quest for finitely presented expansions
expansion of algebraic systems. such as transforming groups into rings or introducing automorphisms. is an important technique in algebra, model theory, and theoretical computer science. Bergstra and Tucker proved that all computably enumerable algebraic systems with decidable word problems have finitely presented expansions. They, along with Goncharov, independently asked if every f.g, computably enumerable algebraic system has a finitely presented expansion. In this talk. we provide examples of f.g. computably enumerable semigroups, groups, and algebras that lack finitely presented expansions, thus answering the question of Bergstra-Tucker and Goncharov. Additionally, we construct examples of residually finite, infinite, and algorithmically finite group, answering Miasnikov and Osin’s question. These constructions rely on the interplay between key concepts from computability (e.g., simple and immune sets) and algebra (e.g., residual finiteness and the GolodShafaverevich theorem).

This work is joint with A. Miasnikov.

Speaker Bio

Bakh Khoussainov，教授，新西兰院士，电子科技大学计算机学院全职教授（我国西部地区引进的第一位发达国家的院士），目前担任电子科技大学算法与逻辑团队主任。他长期从事理论计算机科学中计算与逻辑领域的研究工作，2005年被新西兰最顶尖权威的学术组织——新西兰皇家学会评选为新西兰皇家学会院士，被评价为“在逻辑与理论计算机科学领域的领先专家，工作涉及对可计算性和复杂性理论的深入和非常广泛的研究”。2019年获得德国洪堡研究奖，该奖项旨在授予在基础研究、理论创新、学科引领等方面上取得了卓越成就的研究者。同年他还获得伦敦数学学会与新西兰数学学会联合授予的唯一Aitken Lecturer称号，该荣誉称号每两年仅授予一名最具杰出贡献的新西兰数学家（截至目前仅有包括美国工业与应用数学学会会士（SIAM Fellow）Hinke Osinga教授在内的5位研究者获此殊荣）。2017年他因其对于奇偶博弈问题的突出贡献荣获CCF A类会议ACM STOC 2017年最佳论文奖。他还曾获得新西兰数学学会研究奖，此奖项为新西兰数学领域最高奖，每年仅颁发给一名新西兰数学家，该奖项还曾颁发给包括美国数学学会会士G. Martin, R. Downey教授（AMS Fellow）, M. Conder教授（AMS Fellow）等优秀数学家。

Online Access

Online, Tencent Meeting: 486-877-316

Poster

This talk discusses the parameterized complexity of scheduling problems,

assuming precedence constraints, time windows and typed tasks resource

constraints. We recall the usual parameters used for scheduling problems

and focus on a parameter suitable for problems with time windows, the

pathwitdth of the underlying interval graph. We present three results

involving this parameter. First we show a fixed parameter tractable

(FPT) algorithm for a scheduling problem with unit processing times.

Then, a para-NP-Hardness result assuming arbitrary processing times and

finally we outline a FPT algorithm for this problem by considering two

parameters. Authors: Claire Hanen and Alix Munier-Kordon.

在自动化仓储系统中，高效地完成存储和取出的操作有极大的意义。一个存储的操作是从任意一个入口拿到物品，放到对应的储存空间里一个特定的位置。一个取出的操作是从一个储存空间的特定的位置拿到物品，放到任意一个出口。将存储的操作和取出的操作对应起来，一次性完成，可以减少一些时间，而存储的顺序不同也可以改变耗时。如何在最短时间内完成所有的存储操作是一个重要的问题，这个问题等价于某一类型图上的高多重性非对称旅行商问题，而旅行商问题是经典的NP-hard的问题。然而，这类型图很特殊：存在一个常数大小的集合，使得任何长度为2的路径都包含这个顶点集中的一个顶点。这个报告将描述如何利用这些图的结构特性获得一个多项式时间算法。

Speaker Bio

许超于2021年加入电子科技大学计算机科学与工程学院。现任算法与逻辑团队的助理教授。本科就读于美国纽约州立大学石溪分校数学系，于2018年在伊利诺伊大学香槟分校获得计算机博士学位。毕业后曾在多个科技和对冲基金公司担任研发科学家和软件工程师。研究方向为组合优化和算法的基础研究，相关工作发表于SODA, SICOMP, Mathematical Programming等算法和优化的知名会议和期刊。

Online Access

Online, Tencent Meeting: 939-212-933

Poster

The minimum violation problem asks for a vertex map from a digraph to a pattern digraph that minimizes violation, the total weight of the edges not mapped to an edge. We are interested in surjective mappings. We characterize all patterns where a minimum violation map that fixes some vertices can be computed in polynomial time. We also make progress in the case where we do not fix any vertex in the mapping, including when the digraph is disconnected, when the graph is in the variety of finite paths. Moreover, we obtain a dichotomy result for trees. We apply the result to some cut problems including $k$-cut with size lower bounds and length bounded $k$-cuts. This is a joint work with Ken-ichi Kawarabayashi.

Speaker Bio

Chao Xu is currently an Assistant Professor at Algorithms and Logic Group in UESTC. He obtained a Ph.D. degree of Computer Science at UIUC in May 2018. He works in the field of combinatorial optimization and has published a series of papers in SODA, RANDOM, SIAM J.Computing, SIAM J. Disc Math., Math. Program.

We study the submodular $k$-partition problem. That is, given a finite set $V$ and a submodular function $f:2^V\to \R$, computing a $k$-partition $\{ V_1, \ldots, V_k \}$ of $V$ with the minimum $\sum_{i=1}^k f(V_i)$. The problem is a natural generalization of the minimum $k$-cut problem in graphs and hypergraphs. It is known that the problem is NP-hard for general $k$, and solvable in polynomial time for fixed $k \leq 3$. We construct the first polynomial-time algorithm for the minimum $4$-partition problem.
This is joint work with Tsuyoshi Hirayama, Yuhao Liu, Kazuhisa Makino and Ke Shi.

Speaker Bio

Chao Xu is currently an Assistant Professor at Algorithms and Logic Group in UESTC. He obtained a Ph.D. degree of Computer Science at UIUC in May 2018. He works in the area of combinatorial optimization, algorithms and computational geometry.

Livestream

Online:

https://live.bilibili.com/22051279

https://www.youtube.com/channel/UCkbCc-9vJXb4RZQA0wOPoTw/live

Combinatorial optimization plays an important role in AI and real life. However, many optimization problems are NP hard, that is to say, there is no polynomial-time algorithm for them under reasonable assumptions. In practice, we have designed fast heuristic algorithms and exact algorithms for many of these problems, and they have a very good performance on tested benchmark instances. On the other hand, theoretical algorithms, may not be so practical, solve the problems with theoretical guarantees of running-time bound and solution quality, etc. In this talk, I will discuss the differences between theoretical and practical algorithms, and take the maximum independent set problem as an example to introduce exact algorithms with theoretical running-time bounds.

Speaker Bio

2008年在香港中文大学获得计算机博士学位之后进入电子科技大学工作，现在为电子科技大学计算机学院教授，副院长。主要从事算法分析与设计、机制设计与博弈论、人工智能中的基础算法理论等方向的研究，在Information and Computation、JCSS、Algorithmica、ACM/IEEE Trans.、ICALP、IJCAI、AAAI、WWW、INCOFOM等算法、人工智能领域顶级期刊和会议上发表论文超过100篇，撰写英文专著1部，主持（完成）国家自然科学基金项目5项。是参数算法和精确算法国内外知名的学者。

松弛团指的是近似完全图的图结构，是图论和组合优化领域的经典模型。松弛团模型在数据挖掘，人工智能领域有着重要的应用，而如何从大规模的图中挖掘大型松弛团则是这类应用均需解决共性问题。在本次报告中，我们将从算法工程的角度来介绍松弛团挖掘问题的分析和求解。具体来说，我们将介绍松弛团问题的背景、应用并重点介绍基于分支算法的松弛团问题理论及实践。我们还将以k-plex，最密子图等松弛团为例，介绍这类问题的当前最新的优化结果。

Host

Management School in Northwestern Polytechnical University

HCP (Workshop on Hard Computational Problems: Theory , Algorithms and Applications)

Agenda

For more information, Click here.

How to effectively solve the global optimization problem is always an inevitable problem in scientific research and engineering practice. Evolutionary algorithm is a random search algorithm based on population and independent of derivative, which can effectively solve complex optimization problems. Differential evolution algorithm is a branch of evolutionary algorithm, which has attracted extensive attention due to its good convergence and easy implementation. It has become one of the most popular random search algorithms and has been successfully applied to solve various optimization problems. We study the global search and local search ability and the selection of its mutation strategy in differential evolution algorithm, and evaluate it on the benchmark set of global optimization problem, and prove that the improved differential evolution algorithm has better performance compared with related algorithms.

Speaker Bio

王祖玲，杭州师范大学硕士研究生，主要研究方向为智能进化算法。通过改进相关进化算法，在公认的基准函数(单模态，多模态)上进行实验，结果表明所提出的算法的有效性和可行性。目前已在Information Sciences（SCI 一区）以第一作者发表论文一篇。

Online Meeting

报告形式：线上会议

报告平台：腾讯会议（会议ID：335-281-241）

命题逻辑可满足性问题（简称SAT）是第一个被证明为NP完全的问题，也是计算机科学的一个核心问题。SAT求解器在包括EDA，密码学，资源分配等多个实际场景中有重要应用。求解SAT的主要方法包括基于冲突学习的完备算法和基于局部搜索的不完备算法。SAT领域一个挑战就是如何结合两者优势设计高效混合算法。本报告将回顾作者在此方向的一些探索和结果。

Schedule

2021年12月2日 15:00-16:30
– 09:15 – 16:40 (Time in Beijing)
– December 2, 2021 (Thursday)

Online Meeting

报告形式：线上会议

报告平台：腾讯会议（会议ID：169 500 126）

2021网络经济博弈论坛是网络、计算经济学及博弈论等相关主题的单日研讨会，首届将于2021年11月13日在线举办。论坛由北京大学前沿计算研究中心和苏州科技大学城市发展智库联合主办，聚焦于算法博弈论、信息与计算社会科学、互联网经济学、网络博弈等相关的前沿研究。

本届论坛主要以特邀报告形式进行，将邀请网络博弈以及计算经济学领域的国内外专家和研究人员带来多场精彩报告。

Speakers

Yuqing Kong(Peking University)

Bo Li(Peking University)

Boyu Zhang(Beijing Normal University)

Qi Qi(Renmin University of China)

Jianwei Huang(The Chinese University of Hong Kong, Shenzhen)

Xiao Liu(Tsinghua University)

Zhiyi Huang(The University of Hong Kong)

Registration

Registration is required to participate in the online conference.
Link: https://mp.weixin.qq.com/s/m6K2RlBlcU7YqOKL4Sre-w

Branch and Bound (BnB) is a powerful technique that has been successfully used to solve many combinatorial optimization problems. However, MaxSAT is a notorious exception because BnB MaxSAT solvers perform poorly on many instances encoding interesting real-world and academic optimization problems. This has formed a prevailing opinion in the community stating that BnB is not so useful for MaxSAT, except for random and some special crafted instances. In fact, there has been no advance allowing to significantly speed up BnB MaxSAT solvers in the past few years, as illustrated by the absence of BnB solvers in the annual MaxSAT Evaluation since 2017. Our work aims to change this situation and proposes a new BnB MaxSAT solver, called MaxCDCL, by combining clause learning and an efficient bounding procedure. The experimental results show that, contrary to the prevailing opinion, BnB can be competitive for MaxSAT. MaxCDCL is ranked among the top 5 solvers of the 15 solvers that participated in the 2020 MaxSAT Evaluation, solving a number of instances that other solvers cannot solve. Furthermore, MaxCDCL, when combined with the best existing solvers, solves the highest number of instances of the MaxSAT Evaluations.

Host

HCP

Online Meeting

腾讯会议 ID: 148 668 344

The well-known 1-2-3 conjecture asserts that any graph
with no isolated edges has an edge-weighting vertex colouring using
weights 1,2 and 3. The list version of this conjecture asserts that if each
edge $e$ is given a list $L(e)$ of 3 real numbers as permissible weights,
then there is an edge-weighting vertex colouring $f$ using permissible
weights for each edge $e$.
In this talk, I will give a detailed sketch of the proof that if each
edge $e$ is given a list $L(e)$ of 5 permissible weights, then there is an
edge-weighting vertex colouring $f$ using permissible weights from
$L(e)$ for each edge $e$.

Host

Shanghai Center For Mathematical Science

Online Access

Zoom meeting ID: 818 0564 1942 Password: 121323
Link: https://zoom.com.cn/j/81805641942

Poster

Download poster

Weak and strong coloring numbers are a generalization of
the notion of graph degeneracy to longer distances. We survey some
interesting results and applications of these concepts.

Online Access

Zoom meeting ID: 878 5040 3141 Password: 121323
Link: https://zoom.com.cn/j/87850403141

Poster

Download poster

In a score aggregation system, several agents give scores to a set of candidates independently, and we are going to combine the individual scores to get a final score for each candidate. This is a fundamental problem with a broad range of applications in social choice and many other areas. The simple and commonly used method is to sum up (or average) all scores of each candidate. In this talk, we will give good algebraic and geometric explanations for score aggregation, and introduce a new aggregation model based on the spectral method.

Some results of this talk were published on IJCAI 2017 and AAMAS 2018.

Online Meeting

ZOOM Conference ID: 748 677 4340

Deciding whether a graph contains a $k$-Clique is a well-known NP-hard problem.
One approach to dealing with NP-hard problem is approximation algorithm. However, assuming NP $\ne$ P,
no polynomial time algorithm can approximate $k$-Clique to any factor within $n^{1-\epsilon}$. Another approach
is FPT-algorithm, i.e. algorithm with running time upper bounded by $f(k)\operatorname{poly}(n)$ for some computable
function $f$. Unfortunately, assuming W[1] $\ne$ FPT, the $k$-Clique problem has no FPT-algorithm.
A natural question is: Is there any FPT-algorithm that can approximate $k$-Clique to $1-\epsilon$?
We give a negative answer to this question under the assumption that $k$-Clique problem has no FPT-algorithm.

Speaker Bio

Bingkai Lin is a professor in the Theory Group in the Department of Computer Science and Technology at Nanjing University. Prior to joining Nanjing University, he was a researcher at National Institute of Informatics. He obtained his PhD degree at the University of Tokyo in 2016. He received his Master and Bachelor’s degree at Shanghai Jiao Tong University in 2013 and 2010 respectively. His primary research interests are parameterized complexity and algorithms.

Online Meeting

ZOOM ID: 467 156 1455

Password: 图灵机被提出的年份（4位）

Livestream

http://live.bilibili.com/22528138

Under the hypothesis $P \ne NP$, NP-complete problems cannot be solved in polynomial time. Under ETH, the SAT problem (the first NP-complete problem) cannot be solved in sub-exponential time. Under SETH, the SAT problem has not algorithms with running time better than the trivial bound $O(2^n)$, where $n$ is the number of variables in the formula. However, there are some NP-complete problems that allow algorithms with running time bound much better than the trivial bound $O(2^n)$, and some NP-complete problems that can be solved in sub-exponential time even when ETH holds. In this talk, we will introduce some techniques to design algorithms breaking the border of $O(2^n)$ and also to design sub-exponential algorithms.

Host

Institute for Interdisciplinary Information Sciences, Tsinghua University

A subgraph of an edge-colored graph is rainbow if all of its edges have different colors. For a given graph $H$, the anti-Ramsey number $\operatorname{AR}(n,H)$ of $H$ is the maximum number of colors in an edge-colored $K_n$ such that $K_n$ does not contain a copy of rainbow $H$. We determine the exactly anti-Ramsey number for paths. This confirms aconjecture posed by Erdös, Simonovits and Sós in 1970s.

Host

SCMS （上海数学中心）

Online Meeting

ID: 830 305 307 Password: 121323

https://zoom.com.cn/j/8303053077

Poster

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We survey polynomial-time sparsification for NP-complete Boolean Constraint Satisfaction Problems (CSPs). The goal in sparsification is to reduce the number of constraints in a problem instance without changing the answer, such that a bound on the number of resulting constraints can be given in terms of the number of variables n. We investigate how the worst-case sparsification size depends on the types of constraints allowed in the problem formulation (the constraint language), and how sparsification algorithms can be obtained by modeling constraints as low-degree polynomials. We also consider the corresponding problem for Maximum CSP problems, where the notion of characteristic polynomials turns out to characterize optimal compressibility.

Schedule

• 5:00 p.m., February 25, 2021(Time in Bergen, GMT+1)
• 12:00 p.m., February 25, 2021(Time in Beijing, GMT+8)

Online Meeting

• zoom: https://uib.zoom.us/j/4231169675
• password: CLIQUE