Yi Wang

Bio: Yi Wang is an academic researcher. The author has contributed to research in topics: Flow network & Spare part. The author has an hindex of 2, co-authored 2 publications receiving 69 citations.

Spare-Capacity Assignment For Line Restoration Using a Single-Facility Type

Abstract: The network restoration problem is a specialized capacitated network design problem requiring the installation of spare capacity to fully restore disrupted network flows if any edge in a telecommunications network fails. We present a new mixed-integer programming formulation for a line restoration version of the problem using a single type of capacitated facility. We examine two different models, for distinct and integrated spare-capacity systems, reflecting technologies used in synchronous transfer mode (STM) and asynchronous transfer mode (ATM) networks. The problem is NP-complete in the strong sense. We study the problem's polyhedral structure to identify strong valid inequalities that tighten the problem formulation. Our computational results on several real and randomly generated problems show that these inequalities considerably reduce the integrality gap from an average of 10% to an average of under 1%. These results indicate that strong cutting planes combined with branch-and-bound can provide efficient algorithms for solving a class of real-world problems in the telecommunications industry.

Telecommunication Link Restoration Planning with Multiple Facility Types

Abstract: To ensure uninterrupted service, telecommunication networks contain excess (spare) capacity for rerouting (restoring) traffic in the event of a link failure. We study the NP-hard capacity planning problem of economically installing spare capacity on a network to permit link restoration of steady-state traffic. We present a planning model that incorporates multiple facility types, and develop optimization-based heuristic solution methods based on solving a linear programming relaxation and minimum cost network flow subproblems. We establish bounds on the performance of the algorithms, and discuss problem instances that nearly achieve these worst-case bounds. In tests on three real-world problems and numerous randomly-generated problems containing up to 50 nodes and 150 edges, the heuristics provide good solutions (often within 0.5% of optimality) to problems with single facility type, in equivalent or less time than methods from the literature. For multi-facility problems, the gap between our heuristic solution values and the linear programming bounds are larger. However, for small graphs, we show that the optimal linear programming value does not provide a tight bound on the optimal integer value, and our heuristic solutions are closer to optimality than implied by the gaps.

A cutting plane algorithm for multicomoodity survivable network design problems

Abstract: We present a cutting plane algorithm for solving the following telecommunications network design problem: given point-to-point traffic demands in a network, specified survivability requirements and a discrete cost/capacity function for each link, find minimum cost capacity expansions satisfying the given demands. This algorithm is based on the polyhedral study described in [19]. In this article we describe the underlying problem, the model and the main ingredients in our algorithm. This includes: initial formulation, feasibility test, separation for strong cutting planes, and primal heuristics. Computational results for a set of real-world problems are reported.

Strategic Network Restoration

Abstract: For any networked infrastructure, damage to arcs and/or nodes and associated disruption of network services is inevitable. To reestablish service in a damaged network, affected components must be repaired or reconfigured, a process that can be time consuming and costly, so care must be taken to identify network restoration strategies that reestablish service most efficiently. A strategic goal of service restoration, therefore, is to ensure that facility restoration is prioritized so that system performance is maximized over a planning horizon within budgetary restrictions. To address this problem, this paper proposes a multi-objective optimization approach for network restoration during disaster recovery. The proposed model permits tradeoffs between two objectives, minimization of system cost and maximization of system flow, to be evaluated. A telecommunication application illustrates the significance of the developed approach.

Allocating security resources to a water supply network

Abstract: This paper develops a method for allocating a security budget to a water supply network so as to maximize the network's resilience to physical attack. The method integrates max-min linear programming, hydraulic simulation, and genetic algorithms for constraint generation. The objective is to find a security allocation that maximizes an attacker's marginal cost of inflicting damage through the destruction of network components. We illustrate the method on two example networks, one large and one small, and investigate its allocation effectiveness and computational characteristics.

k-Partition-based facets of the network design problem

Abstract: This article addresses the problem of designing a multicommodity network using facilities of a fixed capacity to satisfy a given set of traffic demands. This problem (called the NDP) arises primarily in the design of high-capacity telecommunication networks. The k-partition of the NDP graph is introduced which results in a smaller k-node NDP. The main result of the article is a theorem, which shows that a facet inequality of the k-node problem translates into a facet of the original problem under a fairly mild condition, that is, the subgraph of each component of the k-partition be connected. This theorem is utilized to show that 2- and 3-partition-based inequalities identified by previous researchers yield families of facets for the original NDP. The structure of the 4-node NDP is explored to derive three different classes of valid inequalities and the conditions under which they are facet defining. The effectiveness of these inequalities is indicated by the computational experience on a 10-node example. © 2006 Wiley Periodicals, Inc. NETWORKS, Vol. 47(3), 123–139, 2006