40597287
A polyhedral study of the generalized vertex packing problem
The traditional vertex packing problem defined on an undirected graph identifies the largest weighted independent set of nodes, that is, a set of nodes whose induced subgraph contains no edges. In this paper, we examine a generalized vertex packing problem (GVP-k) in which k ``violations'' to the independent set restriction are permitted, whereby k edges may exist within the subgraph induced by the chosen set of nodes. A particular context in which such problems arise is in the national airspace planning model of Sherali, Smith, and Trani (2000), where a set of flight-plans need to be composed for various flights subject to conflict, workload, and equity considerations. The GVP-k structure arises in modeling the air-traffic control sector workload restrictions, which stipulate that for each sector and during each discretized time-slot, the number of aircraft conflicts that would need to be resolved should not exceed k, for some k≥1. We derive several classes of facetial valid inequalities for GVP-k for certain specially structured subgraphs, identifying polynomial-sized convex hull representations for some of these cases. Related constraint generation routines are also developed, and some computational results are provided to demonstrate the efficacy of utilizing the proposed valid inequalities in solving GVP-k for different values of k.
41948538
Enhanced Model Representations for an Intra-Ring Synchronous Optical Network Design Problem Allowing Demand Splitting
In this paper, we consider a network design problem arising in the context of deploying synchronous optical networks (SONET) using a unidirectional path switched ring architecture, a standard of transmission using optical fiber technology. Given several rings of this type, the problem is to find an assignment of nodes to possibly multiple rings, and to determine what portion of demand traffic between node pairs spanned by each ring should be allocated to that ring. The constraints require that the demand traffic between each node pair should be satisfiable given the ring capacities, and that no more than a specified maximum number of nodes should be assigned to each ring. The objective function is to minimize the total number of node-to-ring assignments, and hence, the capital investment in add-drop multiplexer equipments. We formulate the problem as a mixed-integer programming model, and propose several alternative modeling techniques designed to improve the mathematical representation of this problem. We then develop various classes of valid inequalities for the problem along with suitable separation procedures for tightening the representation of the model, and accordingly, prescribe an algorithmic approach that coordinates tailored routines with a commercial solver (CPLEX). We also propose a heuristic procedure which enhances the solvability of the problem and provides bounds within 5--13% of the optimal solution. Promising computational results are presented that exhibit the viability of the overall approach and that lend insights into various modeling and algorithmic constructs.
44866557
A Multiple-Criterion Model for Machine Scheduling
We consider a scheduling problem involving a single processor being utilized by two or more customers. Traditionally, such scenarios are modeled by assuming that each customer has the same criterion. In practice, this assumption may not hold. Instead of using a single criterion, we examine the implications of minimizing an aggregate scheduling objective function in which jobs belonging to different customers are evaluated based on their individual criteria. We examine three basic scheduling criteria: minimizing makespan, minimizing maximum lateness, and minimizing total weighted completion time. Although determining a minimum-cost schedule according to any one of these criteria is polynomially solvable, we demonstrate that when minimizing a mix of these criteria, the problem becomes NP-hard.
37305588
A dynamic programming algorithm for the conditional covering problem on tree graphs
In a previous article, we presented algorithms for solving the Conditional Covering Problem (CCP) on path and extended star graphs. The CCP on these graphs can be solved in O(n2) time, where n is the number of nodes in the graph. In this article, we propose a new dynamic programming procedure to solve the CCP on tree graphs. This recursion works from the leaf nodes of the tree up to the root node, using notions of protected and unprotected costs as done for the CCP path algorithm in our previous work. We introduce new preliminary routines and data structures to merge information from subpaths and subtrees, resulting in an O(n4) algorithm to optimally solve the problem. © 2005 Wiley Periodicals, Inc. NETWORKS, Vol. 46(4), 186–197 2005
10698762
Exact and heuristic algorithms for solving the generalized minimum filter placement problem
We consider a problem of placing route-based filters in a communication network to limit the number of forged address attacks to a prescribed level. Nodes in the network communicate by exchanging packets along arcs, and the originating node embeds the origin and destination addresses within each packet that it sends. In the absence of a validation mechanism, one node can send packets to another node using a forged origin address to launch an attack against that node. Route-based filters can be established at various nodes on the communication network to protect against these attacks. A route-based filter examines each packet arriving at a node, and determines whether or not the origin address could be legitimate, based on the arc on which the packet arrives, the routing information, and possibly the destination. The problem we consider seeks to find a minimum cardinality subset of nodes to filter so that the prescribed level of security is achieved. We formulate a mixed-integer programming model for the problem and derive valid inequalities for this model by identifying polynomially-solvable subgraphs of the communication network. We also present three heuristics for solving the filter placement problem and evaluate their performance against the optimal solution provided by the mixed-integer programming model.
27619841
Dynamic programming algorithms for the conditional covering problem on path and extended star graphs
The Conditional Covering Problem (CCP) is a facility location problem on a graph, where the set of nodes represents demand points and potential facility locations. The key aspect of the CCP is that each facility covers all nodes within a given facility-specific coverage radius, except for the node at which it is located. The objective of this problem is to minimize the sum of the facility location costs required to cover all demand points. We first discuss the worst-case complexity of the CCP by examining literature related to the total domination problem, which is a special case of the CCP. Next, we examine the special case of path graphs and provide an O(n2) algorithm for its solution. Finally, we leverage information obtained from this procedure to derive an optimal algorithm for “extended star” graphs (multiple paths having one node in common), without increasing the worst-case complexity of the algorithm. © 2005 Wiley Periodicals, Inc. NETWORKS, Vol. 46(4), 177–185 2005
2766632
On Appropriate Adaptation Levels for the Learning of Gene Linkage
A number of algorithms have been proposed aimed at tackling the problem of learning “Gene Linkage” within the context of genetic optimisation, that is to say, the problem of learning which groups of co-adapted genes should be inherited together during the recombination process. These may be seen within a wider context as a search for appropriate relations which delineate the search space and “guide” heuristic optimisation, or, alternatively, as a part of a comprehensive body of work into Adaptive Evolutionary Algorithms.In this paper, we consider the learning of Gene Linkage as an emergent property of adaptive recombination operators. This is in contrast to the behaviour observed with fixed recombination strategies in which there is no correspondence between the sets of genes which are inherited together between generations, other than that caused by distributional bias. A discrete mathematical model of Gene Linkage is introduced, and the common families of recombination operators, along with some well known linkage-learning algorithms, are modelled within this framework. This model naturally leads to the specification of a recombination operator that explicitly operates on sets of linked genes.Variants of that algorithm, are then used to examine one of the important concepts from the study of adaptivity in Evolutionary Algorithms, namely that of the level (population, individual, or component) at which learning takes place. This is an aspect of adaptation which has received considerable attention when applied to mutation operators, but which has been paid little attention in the context of adaptive recombination operators and linkage learning. It is shown that even with the problem restricted to learning adjacent linkage, the population based variants are not capable of correctly identifying building blocks. This is in contrast to component level adaptation which outperforms conventional operators whose bias is ideal for the problems considered.
577324
Exploring image functionalities in WWW applications development of image/video search and editing engines
Image technologies provide critical components for achieving various Web-based multimedia applications. We identify key technical challenges in today's image/video applications on the WWW. We present two prototype systems, a video search engine (WebSEEk) and a compressed video editor (WebClip), to demonstrate technical challenges and viable solutions. We also discuss major issues in developing next-generation, scalable solutions for large-scale, distributed on-line environments.
15030600
Support for Distributed Pair Programming in the Transparent Video Facetop
The Transparent Video Facetop is a novel user interface concept that supports not only single-user interactions with a PC, but also close pair collaborations, such as that found in collaborative Web browsing, remote medicine, and in distributed pair programming. In this paper we discuss the use of a novel video-based UI called the Facetop [16] for solving several problems reported to us by teams doing distributed pair programming. Specifically, the Facetop allows a distributed pair to recapture some the facial expressions and face-to-face communications contact lost in earlier distributed sessions. It also allows members of a distributed pair to point conveniently, quickly, and naturally to their shared work, in the same manner (manually) that they do when seated side-by-side. Our results enhance the ability of organizations to do effective XP-style agile development with distributed teams.
17817110
MPEG-7 video automatic labeling system
In this demo, we show a novel end-to-end video automatic labeling system, which accepts MPEG-1 sequence inputs and generates MPEG-7 XML metadata files. Detections are based on the prior established anchor models. This system has two parts: model training process and labeling process. They are comprised of seven modules: Shot Segmentation, Region Segmentation, Annotation, Feature Extraction, Model Learning, Classification, and XML Rendering.
3042095
Measuring the Robustness of Resource Allocations in a Stochastic Dynamic Environment
Heterogeneous distributed computing systems often must operate in an environment where system parameters are subject to uncertainty. Robustness can be defined as the degree to which a system can function correctly in the presence of parameter values different from those assumed. We present a methodology for quantifying the robustness of resource allocations in a dynamic environment where task execution times are stochastic. The methodology is evaluated through measuring the robustness of three different resource allocation heuristics within the context of a stochastic dynamic environment. A Bayesian regression model is fit to the combined results of the three heuristics to demonstrate the correlation between the stochastic robustness metric and the presented performance metric. The correlation results demonstrated the significant potential of the stochastic robustness metric to predict the relative performance of the three heuristics given a common objective function.