Approximation algorithms for NP-hard problems

网络设计、网络流和图连通性是理论计算机科学、运筹学和组合优化的核心主题。许多重要的算法范例都是在这些主题的背景下发展起来的，例如最小生成树的贪心算法和网络流的最大流最小割定理。此外，这些主题还出现在许多实际环境中，如容错通信网络的设计和城市道路交通的拥塞控制。在实际环境中出现的许多问题都是np困难的。这意味着不能在合理的运行时间内计算出最优解，对P .not取模。= NP猜想。因此，研究集中在近似算法上，即在最优解的保证因子范围内找到解的高效算法。**我目前和计划的研究主要集中在以下三个广泛的相互关联的主题。我将讨论以下两个主题，我的提案将全面讨论所有主题。近似最小成本网络的设计，包括旅行推销员问题及其变体。**2。基于节点连通性要求的网络设计。**3。非对称TSP的提升-项目方法及相关问题。在所有离散优化中最著名的问题是TSP问题。最著名的算法结果是1976年由Christofides提出的3/2近似算法。长期以来，人们一直推测存在TSP的4/3近似算法，并且存在称为s-t路径TSP的变体的3/2近似算法。**我正在研究的关于这个主题的两个突出的开放问题如下：**(*)改进了称为GRAPHIC TSP的重要特殊情况的7/5的近似保证，可能基于lp舍入技术和耳分解技术的组合。**(*)改进了s-t路径TSP的8/5近似保证，可能基于LP舍入技术，并改进了LP解支持图上的结构结果。**我研究的第二个广泛主题涉及受节点连接要求约束的网络设计。网络设计的一个基本问题是在给定的网络G中找到一个最小代价的子网络H，使H满足一些预先规定的连通性要求。符合边缘连接要求的最低成本网络设计领域在20世纪90年代蓬勃发展，并取得了许多具有里程碑意义的成果。尽管已经进行了十多年的积极研究，但在节点连接要求的类似问题上，进展要慢得多。最近，在与L.Vegh （Proc. IEEE FOCS 2013）合著的一篇论文中，我在该领域的一个基本问题上取得了重大进展：我们有一个最小代价k节点连接生成子图问题的6近似算法，假设节点的数量至少为k^4。我们的研究结果和技术为满足节点连接要求的网络设计开辟了许多新的方向。我计划与研究生和博士后一起继续研究这些课题。**总之，我的研究议程的高级目标是在网络设计领域和组合优化的相关领域提供重大进展。这有可能改善所有在计算科学这一核心领域工作的研究人员可用的结果和技术。像TSP这样的问题在包括加拿大在内的所有现代社会都是普遍存在的；经济和基础设施是建立在物流、运输、网络和稀缺资源对关键任务的最佳分配的基础上的。

Network design, network flows, and graph connectivity occur as core topics in Theoretical Computer Science, Operations Research, and Combinatorial Optimization. Many important algorithmic paradigms were developed in the context of these topics, such as the greedy algorithm for minimum spanning trees and the max-flow min-cut theorem for network flows. Moreover, these topics arise in many practical contexts such as the design of fault-tolerant communication networks and congestion control for urban road traffic. Many of the problems arising in practical contexts are NP-hard. This means that optimal solutions cannot be computed in a reasonable running time, modulo the P .not.= NP conjecture. Hence, research has focused on approximation algorithms, i.e., efficient algorithms that find solutions that are within a guaranteed factor of the optimal solution.**My current and planned research focuses on the following three broad interlocking themes. I discuss two of these topics below, and my proposal discusses all the topics in full.**1. Design of approximately minimum-cost networks, including the Traveling Salesman Problem (TSP) and its variants.**2. Design of networks subject to node-connectivity requirements.**3. Lift-and-Project methods for the Asymmetric TSP and related problems.***The most famous problem in all of discrete optimization is the TSP. The best known algorithmic result is the 3/2-approximation algorithm due to Christofides from 1976. It has long been conjectured that there exists a 4/3-approximation algorithm for the TSP, and that there exists a 3/2-approximation algorithm for a variant called the s-t path TSP.**Two of the outstanding open questions on this topic that I am researching are the following:**(*) Improve on the approximation guarantee of 7/5 for an important special case called the GRAPHIC TSP, possibly based on a combination of LP-rounding techniques and ear-decomposition techniques.**(*) Improve on the approximation guarantee of 8/5 for the s-t path TSP, possibly based on LP-rounding techniques, coupled with improved structural results on the support graph of LP solutions.**The second broad theme of my research addresses the design of networks subject to node-connectivity requirements. One of the basic problems in network design is to find a minimum-cost sub-network H of a given network G such that H satisfies some pre-specified connectivity requirements. The area of minimum-cost network design subject to EDGE-connectivity requirements flourished in the 1990s, and there were a number of landmark results. Progress has been much slower on similar problems with NODE-connectivity requirements, despite more than a decade of active research. Very recently, in a paper co-authored with L.Vegh (Proc. IEEE FOCS 2013), I have obtained a major advance on a fundamental problem in this area: we have a 6-approximation algorithm for the minimum-cost k-node connected spanning subgraph problem, assuming that the number of nodes is at least k^4. Our results and techniques have opened up many new directions in the design of networks subject to node-connectivity requirements. I plan to continue research on these topics, together with graduate students and postdocs.**In summary, the high-level goal of my research agenda is to provide significant advances in the areas of Network Design and related areas of Combinatorial Optimization. This has the potential to improve the results and techniques available to all researchers who work in this core area of the computational sciences. Problems such as the TSP are ubiquitous in all modern societies, including Canada; the economy and infrastructure are based on logistics, transport, networks, and on the optimal allocation of scarce resources to critical tasks.