Single source unsplittable flows with arc-wise lower and upper bounds

In a digraph with a source and several destination nodes with associated demands, an unsplittable flow routes each demand along a single path from the common source to its destination. Given some flow x that is not necessarily unsplittable but satisfies all demands, it is a natural question to ask for an unsplittable flow y that does not deviate from x by too much, i.e., $$y_a\approx x_a$$ y a ≈ x a for all arcs a. Twenty years ago, in a landmark paper, Dinitz et al. (Combinatorica 19:17–41, 1999) proved that there exists an unsplittable flow y such that $$y_a\le x_a+d_{\max }$$ y a ≤ x a + d max for all arcs a, where $$d_{\max }$$ d max denotes the maximum demand value. Our first contribution is a considerably simpler one-page proof for this classical result, based upon an entirely new approach. Secondly, using a subtle variant of this approach, we obtain a new result: There is an unsplittable flow y such that $$y_a\ge x_a-d_{\max }$$ y a ≥ x a - d max for all arcs a. Finally, building upon an iterative rounding technique previously introduced by Kolliopoulos and Stein (SIAM J Comput 31:919–946, 2002) and Skutella (Math Program 91:493–514, 2002), we prove existence of an unsplittable flow that simultaneously satisfies the upper and lower bounds for the special case when demands are integer multiples of each other. For arbitrary demand values, we prove the weaker simultaneous bounds $$x_a/2-d_{\max }\le y_a\le 2x_a+d_{\max }$$ x a / 2 - d max ≤ y a ≤ 2 x a + d max for all arcs a.

Topology-Aware Bus Routing in Complex Networks of Very-Large-Scale Integration with Nonuniform Track Configurations and Obstacles

As one of the most important routing problems in the complex network within a very-large-scale integration (VLSI) circuit, bus routing has become much more challenging when witnessing the advanced technology node enters the deep nanometer era because all bus bits need to be routed with the same routing topology in the context. In particular, the nonuniform routing track configuration and obstacles bring the largest difficulty for maintaining the same topology for all bus bits. In this paper, we first present a track handling technique to unify the nonuniform routing track configuration with obstacles. Then, we formulate the topology-aware single bus routing as an unsplittable flow problem (UFP), which is integrated into a negotiation-based global routing to determine the desired routing regions for each bus. A topology-aware track assignment is also presented to allocate the tracks to each segment of buses under the guidance of the global routing result. Finally, a detailed routing scheme is proposed to connect the segments of each bus. We evaluate our routing result with the benchmark suite of the 2018 CAD Contest. Compared with the top-3 state-of-the-art methods, experimental results show that our proposed algorithm achieves the best overall score regarding specified time limitations.

Safe Approximation—An Efficient Solution for a Hard Routing Problem

The Disjoint Connecting Paths problem and its capacitated generalization, called Unsplittable Flow problem, play an important role in practical applications such as communication network design and routing. These tasks are NP-hard in general, but various polynomial-time approximations are known. Nevertheless, the approximations tend to be either too loose (allowing large deviation from the optimum), or too complicated, often rendering them impractical in large, complex networks. Therefore, our goal is to present a solution that provides a relatively simple, efficient algorithm for the unsplittable flow problem in large directed graphs, where the task is NP-hard, and is known to remain NP-hard even to approximate up to a large factor. The efficiency of our algorithm is achieved by sacrificing a small part of the solution space. This also represents a novel paradigm for approximation. Rather than giving up the search for an exact solution, we restrict the solution space to a subset that is the most important for applications, and excludes only a small part that is marginal in some well-defined sense. Specifically, the sacrificed part only contains scenarios where some edges are very close to saturation. Since nearly saturated links are undesirable in practical applications, therefore, excluding near saturation is quite reasonable from the practical point of view. We refer the solutions that contain no nearly saturated edges as safe solutions, and call the approach safe approximation. We prove that this safe approximation can be carried out efficiently. That is, once we restrict ourselves to safe solutions, we can find the exact optimum by a randomized polynomial time algorithm.

Algorithms as Mechanisms: The Price of Anarchy of Relax and Round

Many algorithms that are originally designed without explicitly considering incentive properties are later combined with simple pricing rules and used as mechanisms. A key question is therefore to understand which algorithms, or, more generally, which algorithm design principles, when combined with simple payment rules such as pay your bid, yield mechanisms with a small price of anarchy. Our main result concerns mechanisms that are based on the relax-and-round paradigm. It shows that oblivious rounding schemes approximately preserve price of anarchy guarantees provable via smoothness. By virtue of our smoothness proofs, our price of anarchy bounds extend to Bayes–Nash equilibria and learning outcomes. In fact, they even apply out of equilibrium, requiring only that agents have no regret for deviations to half their value. We demonstrate the broad applicability of our main result by instantiating it for a wide range of optimization problems ranging from sparse packing integer programs, over single-source unsplittable flow problems and combinatorial auctions with fractionally subadditive valuations, to a maximization variant of the traveling salesman problem.