Identifying positive influence dominating set (PIDS) with the smallest cardinality can produce positive effect with the minimal cost on a social network. The purpose of this article is to propose new approximation alg...
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Identifying positive influence dominating set (PIDS) with the smallest cardinality can produce positive effect with the minimal cost on a social network. The purpose of this article is to propose new approximation algorithms for the minimum PIDS problem and its variants such as the minimum connected PIDS and the minimum PIDS of multiplex networks, with the aim of finding target sets with smaller cardinality. Through the design of novel submodular potential function, we theoretically prove that new approximation algorithms yield approximation ratios with same order compared with existing algorithms. We further demonstrate the performance of our algorithm by showcasing its efficacy on several real-world and publicly available instances of social networks, thereby providing additional evidence that our proposed algorithm can identify PIDS with smaller cardinality.
We study the three-dimensional Knapsack (3DK) problem, in which we are given a set of axis-aligned cuboids with associated profits and an axis-aligned cube knapsack. The objective is to find a non-overlapping axis-ali...
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In the Connected Budgeted maximum Coverage problem (CBC), we are given a collection of subsets S, defined over a ground set X, and an undirected graph G = (V, E), where each node is associated with a set of S. Each se...
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We study the problem of packing element-disjoint Steiner trees in graphs. We are given a graph and a designated subset of terminal nodes, and the goal is to find a maximum cardinality set of element-disjoint trees suc...
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We study the problem of packing element-disjoint Steiner trees in graphs. We are given a graph and a designated subset of terminal nodes, and the goal is to find a maximum cardinality set of element-disjoint trees such that each tree contains every terminal node. An element means a non-terminal node or an edge. (Thus, each non-terminal node and each edge must be in at most one of the trees.) We show that the problem is APX-hard when there are only three terminal nodes, thus answering an open question. Our main focus is on the special case when the graph is planar. We show that the problem of finding two element-disjoint Steiner trees in a planar graph is NP-hard. Similarly, the problem of finding two edge-disjoint Steiner trees in a planar graph is NP-hard. We design an algorithm for planar graphs that achieves an approximation guarantee close to 2. In fact, given a planar graph that is k element-connected on the terminals (k is an upper bound on the number of element-disjoint Steiner trees), the algorithm returns [k/2] - 1 element-disjoint Steiner trees. Using this algorithm, we get an approximation algorithm for the edge-disjoint version of the problem on planar graphs that improves on the previous approximation guarantees. We also show that the natural LP relaxation of the planar problem has an integrality ratio approaching 2.
Given a weighted graph G on n + 1 vertices, a spanning K-tree T-K of G is defined to be a spanning tree T of G together with K distinct edges of G that are not edges of T. The objective of the minimum-cost spanning K-...
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Given a weighted graph G on n + 1 vertices, a spanning K-tree T-K of G is defined to be a spanning tree T of G together with K distinct edges of G that are not edges of T. The objective of the minimum-cost spanning K-tree problem is to choose a subset of edges to form a spanning K-tree with the minimum weight. In this paper, we consider the constructing spanning K-tree problem that is a generalization of the minimum-cost spanning K-tree problem. We are required to construct a spanning K-tree T-K whose n + K edges are assembled from some stock pieces of bounded length L. Let c(0) be the sale price of each stock piece of length L and k(T-K) the number of minimum stock pieces to construct the n + K edges in T-K. For each edge e in G, let c(e) be the construction cost of that edge e. Our new objective is to minimize the total cost of constructing a spanning K-tree T-K, i.e., min(TK) {Sigma(e is an element of TK) c(e) + k(T-K) . c(0)}. The main results obtained in this paper are as follows. (1) A 2-approximation algorithm to solve the constructing spanning K-tree problem. (2) A 3/2-approximation algorithm to solve the special case for constant construction cost of edges. (3) An APTAS for this special case.
We study network-design problems with two different design objectives: the total cost of the edges and nodes in the network and the maximum degree of any node in the network. A prototypical example is the degree-const...
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We study network-design problems with two different design objectives: the total cost of the edges and nodes in the network and the maximum degree of any node in the network. A prototypical example is the degree-constrained node-weighted Steiner tree problem: We are given an undirected graph G(V, E), with a nonnegative integral function d that specifies an upper bound d(v) on the degree of each vertex v is an element of V in the Steiner tree to be constructed, nonnegative costs on the nodes, and a subset of k nodes called terminals. The goal is to construct a Steiner tree T containing all the terminals such that the degree of any node v in T is at most the specified upper bound d(v) and the total cost of the nodes in T is minimum. Our main result is a bicriteria approximation algorithm whose output is approximate in terms of both the degree and cost criteria-the degree of any node v is an element of V in the output Steiner tree is O(d(v)log k) and the cost of the tree is 0(log k) times that of a minimum-cost Steiner tree that obeys the degree bound d(v) for each node v. Our result extends to the more general problem of constructing one-connected networks such as generalized Steiner forests. We also consider the special case in which the edge costs obey the triangle inequality and present simple approximation algorithms with better performance guarantees.
We introduce the Bipartite Multicut problem. This is a generalization of the st-Mincut problem is similar to the Multicut problem and also turns out to be an immediate generalization of the Min UnCut problem. We prove...
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We introduce the Bipartite Multicut problem. This is a generalization of the st-Mincut problem is similar to the Multicut problem and also turns out to be an immediate generalization of the Min UnCut problem. We prove that this problem is NP-hard and then present an SDP based approximation algorithm. The SDP based approximation algorithm uses the structure theorem of l(2)(2) metrics along with region growing techniques. (C) 2010 Elsevier B.V. All rights reserved.
IN lhIS PAPER WE DISCUSS APPROXIM AMON ALGORI1hMS fOR ThE ELEMENT -DISJOINT STEINER TREE PACKING PrObLEM (Element-STP foR show). FOR A GRAPh G = (V, E) AND A subsEr of NODES T c V, CAVED TERMINAL NODES, A STEINER TREE...
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IN lhIS PAPER WE DISCUSS APPROXIM AMON ALGORI1hMS fOR ThE ELEMENT -DISJOINT STEINER TREE PACKING PrObLEM (Element-STP foR show). FOR A GRAPh G = (V, E) AND A subsEr of NODES T c V, CAVED TERMINAL NODES, A STEINER TREE IS A CONNECTED, ACyCLIC SUbGRAPh lhAT CONTAINS AIL1hE TERMINAL NODES IN T. ThE GOAL Of Element-STP IS 10 fiND AS MANY EIEMENT=DISJOINTSTEINERTREES AS POSSIblE. Element-STP IS KNOWN 10 bE P X-hARD EVEN foR right perpendicular vertical bar T vertical bar/2left perpendicular = 3 [I]. IT IS ALSO KNOWN ThAT Element-STP IS NP-hAPD 10 APPROXIMATE WITh vertical bar T vertical bar A fACTOR of n(log M) [3] AND lhERE IS AN O(log vertical bar V vertical bar)-APPROXIMMION ALGORI1hM foR Element-STP [2], [4]. IN lhIS PAPER WE PROVIDE right perpendicular vertical bar T vertical bar/2left perpendicular approximation ALGORI111M foR Element-STP ON GRAPhS WIlh IT I TERMINAL NODES. FURITERMORE, WE ShOW 1hAT1hE approximation RATIO of 3 foR Element-STP ON GRAPhS WI1h fiVE TERM INALNODES CAN bE IMPROVED TO 2.
This article considers the problem of finding a shortest tour to visit viewing sets of points on a plane. Each viewing set is represented as an inverted view cone with apex angle alpha and height h. The apex of each c...
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This article considers the problem of finding a shortest tour to visit viewing sets of points on a plane. Each viewing set is represented as an inverted view cone with apex angle alpha and height h. The apex of each cone is restricted to lie on the ground plane. Its orientation angle (tilt) epsilon is the angle difference between the cone bisector and the ground plane normal. This is a novel variant of the 3D Traveling Salesman Problem with Neighborhoods (TSPN) called Cone-TSPN. One application of Cone-TSPN is to compute a trajectory to observe a given set of locations with a camera: for each location, we can generate a set of cones whose apex and orientation angles alpha and epsilon correspond to the camera's field of view and tilt. The height of each cone h corresponds to the desired resolution. Recently, Plonski and Isler presented an approximation algorithm for Cone-TSPN for the case where all cones have a uniform orientation angle of epsilon=0. We study a new variant of Cone-TSPN where we relax this constraint and allow the cones to have non-uniform orientations. We call this problem Tilted Cone-TSPN and present a polynomial-time approximation algorithm with ratio O(1+tan alpha 1-tan epsilon tan alpha(1+logmax(H)min(H))), where H is the set of all cone heights. We demonstrate through simulations that our algorithm can be implemented in a practical way and that by exploiting the structure of the cones we can achieve shorter tours. Finally, we present experimental results from various agriculture applications that show the benefit of considering view angles for path planning.
Motivated by issues in allocating limited preventative resources to protect a landscape against the spread of a wildfire from a stochastic ignition point, we give approximation algorithms for a new family of stochasti...
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Motivated by issues in allocating limited preventative resources to protect a landscape against the spread of a wildfire from a stochastic ignition point, we give approximation algorithms for a new family of stochastic optimization problems. We study several models in which we are given a graph with edge costs and node values, a budget, and a probabilistic distribution over ignition nodes: the goal is to find a budget-limited set of edges whose removal protects the largest expected value from being reachable from a stochastic ignition node. In particular, 2-stage stochastic models capture the tradeoffs between preventative treatment and real-time response. The resulting stochastic cut problems are interesting in their own right, and capture a number of related interdiction problems, both in the domain of computational sustainability, and beyond. In trees, even the deterministic problem is (weakly) NP hard: we give a Polynomial-time approximation scheme for the single-stage stochastic case in trees when the number of scenarios is constant. For the 2-stage stochastic model in trees we give a -approximation in trees which violates the budget by a factor of at most 2 (delta is the tree diameter), and a 0.387-approximation that is budget-balanced. For the single-stage stochastic case in trees we can save (1- (1 - 1/delta) (delta)) OPT without violating the budget. Single-stage results extend to general graphs with an additional O(log n) loss in budget-balancedness. Multistage results have a similar extension when the number of scenarios is constant. In an extension of the single-stage model where both ignition and spread are stochastic we give a -approximation in trees. Our approximation guarantees in trees also hold for multistage and probabilistic-element-failure generalizations of the Maximum Coverage with Knapsack Constraint problem (MCKP).
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