Label Correcting Methods to Solve Multicriteria Shortest Path Problems

In this paper, we deal with the solution of the multicriteria shortest path problem. In particular, we present a class of labeling methods to generate the entire set of Pareto-optimal path-length vectors from an origin node s to all other nodes in a multicriteria network. The proposed methods are supported theoretically by the principle of optimality and they are defined on the basis of various innovative node and label selection strategies.Computational results comparing the proposed methods to state-of-the-art approaches to solve the problem considered are also reported. They indicate that our methods are competitive in general; in several cases, they outperform all the other codes.     

A Fast Algorithm For Finding A Maximum Free Multiflow In An Inner Eulerian Network And Some Generalizations

be a network, where is an undirected graph with nodes and edges, is a set of specified nodes of , called terminals, and each edge of has a nonnegative integer capacity . If the total capacity of edges with one end at is even for every non-terminal node , then is called inner Eulerian. A free multiflow is a collection of flows between arbitrary pairs of terminals such that the total flow through each edge does not exceed its capacity. In this paper we first generalize a method in Karzanov [11] to find a maximum integer free multiflow in an inner Eulerian network, in time, where is the complexity of finding a maximum flow between two terminals. Next we extend our algorithm to solve the so-called laminar locking problem on multiflows, also in time. We then consider analogs of the above problems in inner balanced directed networks, which means that for each non-terminal node , the sums of capacities of arcs entering and leaving are the same. We show that for such a network a maximum integer free multiflow can be constructed in time, and then extend this result to the corresponding locking problem. Received: March 24, 1997     

Optimal gathering protocols on paths under interference constraints

We study the problem of gathering information from the nodes of a multi-hop radio network into a predefined destination node under reachability and interference constraints. In such a network, a node is able to send messages to other nodes within reception distance, but doing so it might create interference with other communications. Thus, a message can only be properly received if the receiver is reachable from the sender and there is no interference from another message being transmitted simultaneously. The network is modeled as a graph, where the vertices represent the nodes of the network and the edges, the possible communications. The interference constraint is modeled by a fixed integer d≥1, which implies that nodes within distance d in the graph from one sender cannot receive messages from another node. In this paper, we suppose that each node has one unit-length message to transmit and, furthermore, we suppose that it takes one unit of time (slot) to transmit a unit-length message and during such a slot we can have only calls which do not interfere (called compatible calls). A set of compatible calls is referred to as a round. We give protocols and lower bounds on the minimum number of rounds for the gathering problem when the network is a path and the destination node is either at one end or at the center of the path. These protocols are shown to be optimal for any d in the first case, and for 1≤d≤4, in the second case.     

Minimum power multicasting in wireless networks under probabilistic node failures

In this paper we deal with a probabilistic extension of the minimum power multicast (MPM) problem for wireless networks. The deterministic MPM problem consists in assigning transmission powers to the nodes, so that a multihop connection can be established between a source and a given set of destination nodes and the total power required is minimized. We present an extension to the basic problem, where node failure probabilities for the transmission are explicitly considered. This model reflects the necessity of taking uncertainty into account in the availability of the hosts. The novelty of the probabilistic minimum power multicast (PMPM) problem treated in this paper consists in the minimization of the assigned transmission powers, imposing at the same time a global reliability level to the solution network. An integer linear programming formulation for the PMPM problem is presented. Furthermore, an exact algorithm based on an iterative row and column generation procedure, as well as a heuristic method are proposed. Computational experiments are finally presented.     

On the enrouting protocol problem under uncertainty

In this paper we present a two-stage stochastic mixed 0–1 dynamic multicommodity model and algorithm for determining the enrouting protocol in the telecommunications network under uncertainty. Given the network connectivity, node processing and buffer and arc flow capacity, the aim is to determine the outgoing arc for the information flow reaching a given node for each destination terminal node (i.e., obtaining the route to be followed by the information flow from each origin terminal node to each destination terminal node). The origin–destination (O–D) flow matrix is given by the number of information packets to be sent from the origin terminal nodes to the destination terminal nodes along a given time horizon, i.e., a call scale. The uncertainty in the O–D flow matrix is treated via a scenario tree approach. The main goal is to minimize a composite function of the expected lost information, a penalization of the deviation from the FIFO strategy on the information flow entering the network, and the expected number of nodes visited by the information packets. A mixture of an enrouting arc generation scheme and a genetic algorithm for obtaining the enrouting protocols over the scenarios is presented. The tool presented in this paper could be used for simulating the enrouting protocols to analyze the saturation of the network, but it has a time constraint for real time operation. Faster algorithms are needed to define the routing tables during the operation stage. Computational experience is reported.     

Optimising Waiting at Nodes in Time-Dependent Networks: Cost Functions and Applications

In this paper, the relationship between waiting at nodes and the path cost in a transport network is analysed. An exact solution algorithm for generating the shortest path with optimal waiting at the nodes is proposed. The general case is examined, considering a time-dependent network (time influences the cost). To develop a full application, the algorithm is applied in the case of a vehicle routing problem on a real network.     

Joint Modeling of Multiple Network Views

Latent space models (LSM) for network data rely on the basic assumption that each node of the network has an unknown position in a D-dimensional Euclidean latent space: generally the smaller the distance between two nodes in the latent space, the greater their probability of being connected. In this article, we propose a variational inference approach to estimate the intractable posterior of the LSM. In many cases, different network views on the same set of nodes are available. It can therefore be useful to build a model able to jointly summarize the information given by all the network views. For this purpose, we introduce the latent space joint model (LSJM) that merges the information given by multiple network views assuming that the probability of a node being connected with other nodes in each network view is explained by a unique latent variable. This model is demonstrated on the analysis of two datasets: an excerpt of 50 girls from “Teenage Friends and Lifestyle Study” data at three time points and the Saccharomyces cerevisiae genetic and physical protein–protein interactions. Supplementary materials for this article are available online.     

基于攻击传播性的分布式网络信任模型

根据分布式网络的特点及现有网络节点信任模型的不足,提出了基于攻击传播性的分布式网络信任模型。根据恶意节点攻击行为及其攻击传播性的特点,给出了在攻击具有传播性条件下的信任度更新计算方法,结合直接信任度和间接信任度计算出总体信任度,最后给出模型的计算协议及仿真实验。实验结果表明,该模型更逼近真实网络运行情况,并有效地避免恶意节点的攻击,提高文件成功传输的比率。该模型对于分布式网络环境下提高网络节点信任度评价的准确性,建立可信网络传输路径具有重要意义。     

Emergency path restoration problems

We consider the problem of optimally scheduling the restoration of edges of a transportation network destroyed/damaged by a disaster. The restoration is performed by service units (servers) which have fixed restoration speeds. If several servers work simultaneously at the same point of the network, their collective restoration speed is the sum of their individual restoration speeds. The servers are initially located at some nodes. Each server can travel within the already restored part of the network with infinite speed, that is, at any time can immediately relocate to another point of the same connected component of the already restored part of the network. It is required to minimize a scheduling objective that can be expressed as the maximum or the sum of nondecreasing functions of the recovery times of the nodes, where the recovery time of a node is the time when the node is reached for the first time by a server. We present polynomial-time algorithms on path networks for problems with fixed initial locations of the servers. For problems with flexible locations that should also be optimized, we present polynomial-time algorithms for the case of equal restoration speeds of the servers, and prove that the problems are strongly NP-hard if the restoration speeds of the servers can be different.     

Heuristics for Distribution Network Design in Telecommunication

A distribution network problem arises in a lower level of an hierarchical modeling approach for telecommunication network planning. This paper describes a model and proposes a lagrangian heuristic for designing a distribution network. Our model is a complex extension of a capacitated single commodity network design problem. We are given a network containing a set of sources with maximum available supply, a set of sinks with required demands, and a set of transshipment points. We need to install adequate capacities on the arcs to route the required flow to each sink, that may be an intermediate or a terminal node of an arborescence. Capacity can only be installed in discrete levels, i.e., cables are available only in certain standard capacities. Economies of scale induce the use of a unique higher capacity cable instead of an equivalent set of lower capacity cables to cover the flow requirements of any link. A path from a source to a terminal node requires a lower flow in the measure that we are closer to the terminal node, since many nodes in the path may be intermediate sinks. On the other hand, the reduction of cable capacity levels across any path is inhibited by splicing costs. The objective is to minimize the total cost of the network, given by the sum of the arc capacity (cables) costs plus the splicing costs along the nodes. In addition to the limited supply and the node demand requirements, the model incorporates constraints on the number of cables installed on each edge and the maximum number of splices at each node. The model is a NP-hard combinatorial optimization problem because it is an extension of the Steiner problem in graphs. Moreover, the discrete levels of cable capacity and the need to consider splicing costs increase the complexity of the problem. We include some computational results of the lagrangian heuristics that works well in the practice of computer aided distribution network design.     

The computational complexity of the pooling problem

The pooling problem is an extension of the minimum cost flow problem defined on a directed graph with three layers of nodes, where quality constraints are introduced at each terminal node. Flow entering the network at the source nodes has a given quality, at the internal nodes (pools) the entering flow is blended, and then sent to the terminal nodes where all entering flow streams are blended again. The resulting flow quality at the terminals has to satisfy given bounds. The objective is to find a cost-minimizing flow assignment that satisfies network capacities and the terminals’ quality specifications. Recently, it was proved that the pooling problem is NP-hard, and that the hardness persists when the network has a unique pool. In contrast, instances with only one source or only one terminal can be formulated as compact linear programs, and thereby solved in polynomial time. In this work, it is proved that the pooling problem remains NP-hard even if there is only one quality constraint at each terminal. Further, it is proved that the NP-hardness also persists if the number of sources and the number of terminals are no more than two, and it is proved that the problem remains hard if all in-degrees or all out-degrees are at most two. Examples of special cases in which the problem is solvable by linear programming are also given. Finally, some open problems, which need to be addressed in order to identify more closely the borderlines between polynomially solvable and NP-hard variants of the pooling problem, are pointed out.     

An efficient label setting/correcting shortest path algorithm

We design a new label shortest path algorithm by applying the concept of a pseudo permanent label. This approach allows an algorithm to partition the set of nodes into two new sets: pseudo permanently labeled nodes and its complementary set. From this point of view, this new label method can be considered as a label setting method. Moreover, at least one node becomes permanently labeled when some nodes which belong to the set of pseudo permanently labeled nodes are scanned in each iteration of the algorithm. In the case of networks with non-negative length arcs it is easy to prove that this node has the minimum distance label among the non-pseudo permanently labeled nodes. On the other hand, it is not known during the computation which pseudo permanently labeled nodes are permanently labeled. Therefore, all distance labels are temporary and the algorithm becomes a label correcting method. Nevertheless, the proposed algorithm exhibits some nice features, such as: (1) the time bound for the running of the algorithm for a network with n nodes and m arcs is O(nm); (2) the number of node scan operations in the algorithm is less than the number of these operations in the previous label correcting algorithms as is observed in the computational experience; (3) the algorithm incorporates two new rules which allow easy detection of a negative cycle in the network; (4) the algorithm is quite simple and very easy to implement, and does not require sophisticated data structures; (5) the algorithm exhibits flexibility in the order in which the new pseudo permanently labeled nodes are scanned. The above features are possible through the application of the pseudo permanent label concept.     

The energy-constrained quickest path problem

This paper addresses a variant of the quickest path problem in which each arc has an additional parameter associated to it representing the energy consumed during the transmission along the arc while each node is endowed with a limited power to transmit messages. The aim of the energy-constrained quickest path problem is to obtain a quickest path whose nodes are able to support the transmission of a message of a known size. After introducing the problem and proving the main theoretical results, a polynomial algorithm is proposed to solve the problem based on computing shortest paths in a sequence of subnetworks of the original network. In the second part of the paper, the bi-objective variant of this problem is considered in which the objectives are the transmission time and the total energy used. An exact algorithm is proposed to find a complete set of efficient paths. The computational experiments carried out show the performance of both algorithms.     

Exact boundary controllability of partial nodal profile for network of strings

Based on the theory of exact boundary controllability of nodal profile for hyperbolic systems, the authors propose the concept of exact boundary controllability of partial nodal profile to expand the scope of applications. With the new concept, we can shorten the controllability time, save the number of controls, and increase the number of charged nodes with given nodal profiles. Furthermore, we introduce the concept of in-situ controlled node to deal with a new situation that one node can be charged and controlled simultaneously. The minimum number of boundary controls on the entire tree-like network is determined by using the concept of ‘degree of freedom of charged nodes’ introduced. And the concept of ‘control path’ is introduced to appropriately divide the network, so that we can determine the infimum of controllability time. General frameworks of constructive proof are given on a single interval, a star-like network, a chain-like network and a planar tree-like network for linear wave equation(s) with Dirichlet, Neumann, Robin and dissipative boundary conditions to establish a complete theory on the exact boundary controllability of partial nodal profile.     

Isodistant points in competitive network facility location

An isodistant point is any point on a network which is located at a predetermined distance from some node. For some competitive facility location problems on a network, it is verified that optimal (or near-optimal) locations are found in the set of nodes and isodistant points (or points in the vicinity of isodistant points). While the nodes are known, the isodistant points have to be determined for each problem. Surprisingly, no algorithm has been proposed to generate the isodistant points on a network. In this paper, we present a variety of such problems and propose an algorithm to find all isodistant points for given threshold distances associated with the nodes. The number of isodistant points is upper bounded by nm, where n and m are the number of nodes and the number of edges, respectively. Computational experiments are presented which show that isodistant points can be generated in short run time and the number of such points is much smaller than nm. Thus, for networks of moderate size, it is possible to find optimal (or near-optimal) solutions through the Integer Linear Programming formulations corresponding to the discrete version of such problems, in which a finite set of points are taken as location candidates.     

Optimal gossiping in paths and cycles

In the gossiping problem, each node in a network possesses a token initially; after gossiping, every node has a copy of every other node's token. The nodes exchange their tokens by packets. A solution to the problem is judged by how many rounds of packet sending it requires. In this paper, we consider the version of the problem in which a packet is of limited size (a packet can hold up to p tokens), the links (edges) of the network are half-duplex (only one packet can flow through a link at a time), and the nodes are all-port (a node's incident edges can all be active at the same time). We study the path and the cycle which are essential building blocks for more complex structures. We present tight lower bounds and algorithms which match them. The results also lead to the conclusion that p=2 is the optimal packet size.     

Vehicle routing with soft time windows and stochastic travel times: A column generation and branch-and-price solution approach

We study a vehicle routing problem with soft time windows and stochastic travel times. In this problem, we consider stochastic travel times to obtain routes which are both efficient and reliable. In our problem setting, soft time windows allow early and late servicing at customers by incurring some penalty costs. The objective is to minimize the sum of transportation costs and service costs. Transportation costs result from three elements which are the total distance traveled, the number of vehicles used and the total expected overtime of the drivers. Service costs are incurred for early and late arrivals; these correspond to time-window violations at the customers. We apply a column generation procedure to solve this problem. The master problem can be modeled as a classical set partitioning problem. The pricing subproblem, for each vehicle, corresponds to an elementary shortest path problem with resource constraints. To generate an integer solution, we embed our column generation procedure within a branch-and-price method. Computational results obtained by experimenting with well-known problem instances are reported.     

On a matrix-based measure of the degree of coreness of a node in a network

The paper focuses on the right and left eigenvectors of a network matrix that belong to the largest eigenvalue. It is shown that each of vector entries measures the walk centrality of the corresponding node’s position in the network’s link structure and of the positions of the node’s adjacent nodes; as a result, it indicates to which degree the node can be associated with the structure’s core, i.e., the structural coreness of the node. The relationship between the vectors’ coordinates and the position of the nodes, as well as the actual computation of the coordinates, is based on an iterative computational scheme known as the power method. The paper studies the method’s convergence for networks of different structure. Some possible applications are discussed. The paper also includes a numerical example dealing with a real network of 197 nodes and 780 links.     

面向可靠性的网络级联失效分析

本文从可靠性角度定义了影响级联失效过程的关键指标,探讨网络不同类型节点在失效传播过程中的作用及其对可靠性的影响。通过节点聚合描述不同节点的失效传递,以及节点失效时的网络拓扑结构变化特征,从而构建网络级联失效模型,然后确定网络的关键失效路径。最后通过案例分析,发现交通网络在经过聚合变化后稳定性更强,流通性也有提高,验证了该模型的有效性。     

Finding a minimum cost path between a pair of nodes in a time-varying road network with a congestion charge

The minimum cost path problem in a time-varying road network is a complicated problem. The paper proposes two heuristic methods to solve the minimum cost path problem between a pair of nodes with a time-varying road network and a congestion charge. The heuristic methods are compared with an alternative exact method using real traffic information. Also, the heuristic methods are tested in a benchmark dataset and a London road network dataset. The heuristic methods can achieve good solutions in a reasonable running time.