Multicolor routing in the undirected hypercube

An undirected routing problem is a pair (G,R) where G is an undirected graph and R is an undirected multigraph such that V(G)=V(R). A solution to an undirected routing problem (G,R) is a collection P of undirected paths of G (possibly containing multiple occurrences of the same path) such that edges of R are in one-to-one correspondence with the paths of P, with the path corresponding to edge {u,v} connecting u and v. We say that a collection of paths P is k-colorable if each path of P can be colored by one of the k colors so that the paths of the same color are edge-disjoint (each edge of G appears at most once in the paths of each single color). In the circuit-switched routing context, and in optical network applications in particular, it is desirable to find a solution to a routing problem that is colorable with as few colors as possible. Let Q_n denote the n-dimensional hypercube, for arbitrary n1. We show that a routing problem (Q_n,R) always admits a 4d-colorable solution where d is the maximum vertex degree of R. This improves over the 16d/2-color result which is implicit in the previous work of Aumann and Rabani [SODA95, pp. 567–576]. Since, for any positive d, there is a multigraph R of degree d such that any solution to (Q_n,R) requires at least d colors, our result is tight up to a factor of four. In fact, when d=1, it is tight up to a factor of two, since there is a graph of degree one (the antipodal matching) that requires two colors.     

Multiflows and disjoint paths of minimum total cost

In this paper we discuss a number of recent and earlier results in the field of combinatorial optimization that concerns problems on minimum cost multiflows (multicommodity flows) and edge-disjoint paths. More precisely, we deal with an undirected networkN consisting of a supply graphG, a commodity graphH and nonnegative integer-valued functions of capacities and costs of edges ofG, and consider the problems of minimizing the total cost among (i) all maximum multiflows, and (ii) all maximuminteger multiflows. For problem (i), we discuss the denominators behavior in terms ofH. The main result is that ifH is complete (i.e. flows between any two terminals are allowed) then (i) has ahalf-integer optimal solution. Moreover, there are polynomial algorithms to find such a solution. For problem (ii), we give an explicit combinatorial minimax relation in case ofH complete. This generalizes a minimax relation, due to Mader and, independently, Lomonosov, for the maximum number of edge-disjoint paths whose ends belong to a prescribed subset of nodes of a graph. Also there exists a polynomial algorithm when the capacities are all-unit. The minimax relation for (ii) withH complete allows to describe the dominant for the set of (T, d)-joins (extending the notion ofT-join) and the dominant for the set of maximum multi-joins of a graph. Also other relevant results are reviewed and open questions are raised. © 1997 The Mathematical Programming Society, Inc. Published by Elsevier Science B.V.     

Optimizing cost flows by edge cost and capacity upgrade

We examine a network upgrade problem for cost flows. A budget can be distributed among the arcs of the network. An investment on each single arc can be used either to decrease the arc flow cost, or to increase the arc capacity, or both. The goal is to maximize the flow through the network while not exceeding bounds on the budget and on the total flow cost.

The problems are NP-hard even on series-parallel graphs. We provide an approximation algorithm on series-parallel graphs which, for arbitrary δ,>0, produces a solution which exceeds the bounds on the budget and the flow cost by factors of at most 1+δ and 1+, respectively, while the amount of flow is at least that of an optimum solution. The running time of the algorithm is polynomial in the input size and 1/(δ). In addition we give an approximation algorithm on general graphs applicable to problem instances with small arc capacities.     

最小费用k度限制树对策

本在Glover—Klingman算法及最小费用支撑树对策的基础上，讨论了最小费用k度限制树对策问题．利用威胁、旁支付理论制订了两种规则，并利用优超、策略等价理论分别给出了在这两种规则下最小费用k度限制树对策核心中的解，从而证明了在这两种规则下其核心非空．     

Minimum cost homomorphisms to semicomplete multipartite digraphs

For digraphs D and H, a mapping f:V(D)→V(H) is a homomorphism ofDtoH if uv∈A(D) implies f(u)f(v)∈A(H). For a fixed directed or undirected graph H and an input graph D, the problem of verifying whether there exists a homomorphism of D to H has been studied in a large number of papers. We study an optimization version of this decision problem. Our optimization problem is motivated by a real-world problem in defence logistics and was introduced recently by the authors and M. Tso.Suppose we are given a pair of digraphs D,H and a cost c_i(u) for each u∈V(D) and i∈V(H). The cost of a homomorphism f of D to H is ∑_u∈V(D)c_f(u)(u). Let H be a fixed digraph. The minimum cost homomorphism problem for H, MinHOMP(H), is stated as follows: For input digraph D and costs c_i(u) for each u∈V(D) and i∈V(H), verify whether there is a homomorphism of D to H and, if it does exist, find such a homomorphism of minimum cost. In our previous paper we obtained a dichotomy classification of the time complexity of when H is a semicomplete digraph. In this paper we extend the classification to semicomplete k-partite digraphs, k≥3, and obtain such a classification for bipartite tournaments.     

Minimum cut bases in undirected networks

Given an undirected, connected network G=(V,E) with weights on the edges, the cut basis problem is asking for a maximal number of linear independent cuts such that the sum of the cut weights is minimized. Surprisingly, this problem has not attained as much attention as another graph theoretic problem closely related to it, namely, the cycle basis problem. We consider two versions of the problem: the unconstrained and the fundamental cut basis problem.For the unconstrained case, where the cuts in the basis can be of an arbitrary kind, the problem can be written as a multiterminal network flow problem, and is thus solvable in strongly polynomial time. In contrast, the fundamental cut basis problem, where all cuts in the basis are obtained by deleting an edge, each from a spanning tree T, is shown to be NP-hard. In this proof, we also show that a tree which induces the minimum fundamental cycle basis is also an optimal solution for the minimum fundamental cut basis problem in unweighted graphs.We present heuristics, integer programming formulations and summarize first experiences with numerical tests.     

On equivalent representations of certain multicommodity networks as single commodity flow problems

Several classes of multicommodity networks have been shown to have the property that they can be transformed to equivalent uncapacitated single commodity flow problems. We show that many of these networks can be further reduced to smaller, semi-capacitated flow problems using the inverse of a result of Ford and Fulkerson. This appears to be a useful computationally-oriented tool for developing practically efficient algorithms. These concepts are also used to establish a generalization of a previous result concerning multicommodity transportation problems.     

New algorithms for convex cost tension problem with application to computer vision

Motivated by various applications to computer vision, we consider the convex cost tension problem, which is the dual of the convex cost flow problem. In this paper, we first propose a primal algorithm for computing an optimal solution of the problem. Our primal algorithm iteratively updates primal variables by solving associated minimum cut problems. We show that the time complexity of the primal algorithm is $O(K?T(n,m))$, where $K$ is the range of primal variables and $T(n,m)$ is the time needed to compute a minimum cut in a graph with $n$ nodes and $m$ edges. We then develop an improved version of the primal algorithm, called the primal–dual algorithm, by making good use of dual variables in addition to primal variables. Although its time complexity is the same as that of the primal algorithm, we can expect a better performance in practice. We finally consider an application to a computer vision problem called the panoramic image stitching.     

An introduction to dynamic generative networks: Minimum cost flow

What we are dealing with is a class of networks called dynamic generative network flows in which the flow commodity is dynamically generated at source nodes and dynamically consumed at sink nodes. As a basic assumption, the source nodes produce the flow according to time generative functions and the sink nodes absorb the flow according to time consumption functions. This paper tries to introduce these networks and formulate minimum cost dynamic flow problem for a pre-specified time horizon T. Finally, some simple, efficient approaches are developed to solve the dynamic problem, in the general form when the capacities and costs are time varying and some other special cases, as a minimum cost static flow problem.     

Maximizing the minimum source-sink path subject to a budget constraint

Given a linear cost function for lengthening arcs, a technique is shown for maximizing, within a budget, the shortest source—sink path length in a graph. The computation is equivalent to the parametric solution of a minimum cost flow problem.This work was done while G.C. Harding was at Cornell University.The work of D.R. Fulkerson was supported by the National Science Foundation under Grant MPS74-24026 and by the Office of Naval Research under Grant NR 044-439.     

Minimum principle for systems with boundary conditions and cost having Stieltjes-type integrals

Pontryagin's minimum principle for nonlinear differential systems with Stieltjes boundary constraints and performance index with an integral of the Lebesgue-Stieltjes type is derived. The case of infinite time is also considered.     

Single-path routing of stochastic flows in networks

The paper revisits a very simple network routing and dimensioning model, with two specific assumptions: the traffic amounts to be routed are Gaussian random variables, and each commodity must use one single route in the network. The need to control congestion leads naturally to probabilistic constraints. The impact of stochastic assumptions on solution algorithms is investigated, when compared to the usual deterministic case.     

Fast deterministic approximation for the multicommodity flow problem

In this paper we consider an optimization version of the multicommodity flow problem which is known as the maximum concurrent flow problem. We show that an approximate solution to this problem can be computed deterministically using O(k(ε ⁻² + logk) logn) 1-commodity minimum-cost flow computations, wherek is the number of commodities,n is the number of nodes, andε is the desired precision. We obtain this bound by proving that in the randomized algorithm developed by Leighton et al. (1995) the random selection of commodities can be replaced by the deterministic round-robin without increasing the total running time. Our bound significantly improves the previously known deterministic upper bounds and matches the best known randomized upper bound for the approximation concurrent flow problem. A preliminary version of this paper appeared inProceedings of the 6th ACM-SIAM Symposium on Discrete Algorithms, San Francisco CA, 1995, pp. 486–492.     

A note on the minimum interval cost flow problem

We reduce the problem of minimum interval cost flow problem (MICFP) introduced by Hashemi et al. (2006) to the well-known minimum cost flow problem (MCFP).     

On shortest disjoint paths in planar graphs

For a graph G and a collection of vertex pairs {(s₁,t₁),…,(s_k,t_k)}, the k disjoint paths problem is to find k vertex-disjoint paths P₁,…,P_k, where P_i is a path from s_i to t_i for each i=1,…,k. In the corresponding optimization problem, the shortest disjoint paths problem, the vertex-disjoint paths P_i have to be chosen such that a given objective function is minimized. We consider two different objectives, namely minimizing the total path length (minimum sum, or short: Min-Sum), and minimizing the length of the longest path (Min-Max), for k=2,3.Min-Sum: We extend recent results by Colin de Verdière and Schrijver to prove that, for a planar graph and for terminals adjacent to at most two faces, the Min-Sum 2 Disjoint Paths Problem can be solved in polynomial time. We also prove that, for six terminals adjacent to one face in any order, the Min-Sum 3 Disjoint Paths Problem can be solved in polynomial time.Min-Max: The Min-Max 2 Disjoint Paths Problem is known to be NP-hard for general graphs. We present an algorithm that solves the problem for graphs with tree-width 2 in polynomial time. We thus close the gap between easy and hard instances, since the problem is weakly NP-hard for graphs with tree-width 3.     

A polynomial time primal network simplex algorithm for minimum cost flows

Developing a polynomial time primal network simplex algorithm for the minimum cost flow problem has been a long standing open problem. In this paper, we develop one such algorithm that runs in O(min(n ²m lognC, n ²m² logn)) time, wheren is the number of nodes in the network,m is the number of arcs, andC denotes the maximum absolute arc costs if arc costs are integer and ∞ otherwise. We first introduce a pseudopolynomial variant of the network simplex algorithm called the “premultiplier algorithm”. We then develop a cost-scaling version of the premultiplier algorithm that solves the minimum cost flow problem in O(min(nm lognC, nm ² logn)) pivots. With certain simple data structures, the average time per pivot can be shown to be O(n). We also show that the diameter of the network polytope is O(nm logn).     

On the core of cost-revenue games: Minimum cost spanning tree games with revenues

In this paper, we analyze cost sharing problems arising from a general service by explicitly taking into account the generated revenues. To this cost-revenue sharing problem, we associate a cooperative game with transferable utility, called cost-revenue game. By considering cooperation among the agents using the general service, the value of a coalition is defined as the maximum net revenues that the coalition may obtain by means of cooperation. As a result, a coalition may profit from not allowing all its members to get the service that generates the revenues. We focus on the study of the core of cost-revenue games. Under the assumption that cooperation among the members of the grand coalition grants the use of the service under consideration to all its members, it is shown that a cost-revenue game has a nonempty core for any vector of revenues if, and only if, the dual game of the cost game has a large core. Using this result, we investigate minimum cost spanning tree games with revenues. We show that if every connection cost can take only two values (low or high cost), then, the corresponding minimum cost spanning tree game with revenues has a nonempty core. Furthermore, we provide an example of a minimum cost spanning tree game with revenues with an empty core where every connection cost can take only one of three values (low, medium, or high cost).     

Path problems in generalized stars, complete graphs, and brick wall graphs

Path problems such as the maximum edge-disjoint paths problem, the path coloring problem, and the maximum path coloring problem are relevant for resource allocation in communication networks, in particular all-optical networks. In this paper, it is shown that maximum path coloring can be solved optimally in polynomial time for bidirected generalized stars, even in the weighted case. Furthermore, the maximum edge-disjoint paths problem is proved NP-hard for complete graphs (undirected or bidirected), a constant-factor off-line approximation algorithm is presented for the weighted case, and an on-line algorithm with constant competitive ratio is given for the unweighted case. Finally, an open problem concerning the existence of routings that simultaneously minimize the maximum load and the number of colors is solved: an example for a graph and a set of requests is given such that any routing that minimizes the maximum load requires strictly more colors for path coloring than a routing that minimizes the number of colors.     

Estimation of flows in flow networks

Let G be a directed graph with an unknown flow on each edge such that the following flow conservation constraint is maintained: except for sources and sinks, the sum of flows into a node equals the sum of flows going out of a node. Given a noisy measurement of the flow on each edge, the problem we address, which we call the Most Probable Flow Estimation problem (MPFE), is to estimate the most probable assignment of flow for every edge such that the flow conservation constraint is maintained. We provide an algorithm called ΔY-mpfe for solving the MPFE problem when the measurement error is Gaussian (Gaussian-MPFE). The algorithm works in O(∣E∣ + ∣V∣²) when the underlying undirected graph of G is a 2-connected planar graph, and in O(∣E∣ + ∣V∣) when it is a 2-connected serial-parallel graph or a tree. This result is applicable to any Minimum Cost Flow problem for which the cost function is τ_e(X_e − μ_e)² for edge e where μ_e and τ_e are constants, and X_e is the flow on edge e. We show that for all topologies, the Gaussian-MPFE’s precision for each edge is analogous to the equivalent resistance measured in series to this edge in an electrical network built by replacing every edge with a resistor reflecting the measurement’s precision on that edge.