106215
A stochastic integer programming approach to solving a synchronous optical network ring design problem
We develop stochastic integer programming techniques tailored toward solving a Synchronous Optical Network (SONET) ring design problem with uncertain demands. Our approach is based on an L-shaped algorithm, whose (integer) master program prescribes a candidate network design, and whose (continuous) subproblems relay information regarding potential shortage penalty costs to the ring design decisions. This naive implementation performs very poorly due to two major problems: (1) the weakness of the master problem relaxations, and (2) the limited information passed to the master problem by the optimality cuts. Accordingly, we enforce certain necessary conditions regarding shortage penalty contributions to the objective function within the master problem, along with a corresponding set of valid inequalities that improves the solvability of the master problem. We also show how a nonlinear reformulation of the model can be used to capture an exponential number of optimality cuts generated by the linear model. We augment these techniques with a powerful upper-bounding heuristic to further accelerate the convergence of the algorithm, and demonstrate the effectiveness of our methodologies on a test bed of randomly generated stochastic SONET instances. © 2004 Wiley Periodicals, Inc. NETWORKS, Vol. 44(1), 12–26 2004
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
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.
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
17502763
Alignment Of Protein Structures With A Memetic Evolutionary Algorithm
CATEGORY: Real-World Applications 
 
Structural comparison of proteins is a core problem in modern biomedical research. Identifying structural similarities is essential for the assessment of the relationship between structure and function in proteins, and structural comparison techniques play a key role in applications like rational drug design. In this paper we consider a technique for protein structure comparison known as the maximum contact map overlap problem. In this problem, the similarity between two protein structures is computed by aligning the proteins to maximize the number of shared contacts in their corresponding contact maps. 
 
We present a new approach to this problem that uses a Multimeme evolutionary algorithm. The best solution found by our algorithm provides a lower bound on the value of the optimal structural alignment between the proteins. We have evaluated the Multimeme algorithm on a range of benchmark problems and compared with previous heuristics. We apply a linear programming method, which provides an upper bound, to assess the accuracy of our solutions. Our experiments show that the Multimeme evolutionary algorithm represents a significant improvement on the current state of the art in metaheuristics for this problem.
6223153
Creating models of truss structures with optimization
We present a method for designing truss structures, a common and complex category of buildings, using non-linear optimization. Truss structures are ubiquitous in the industrialized world, appearing as bridges, towers, roof supports and building exoskeletons, yet are complex enough that modeling them by hand is time consuming and tedious. We represent trusses as a set of rigid bars connected by pin joints, which may change location during optimization. By including the location of the joints as well as the strength of individual beams in our design variables, we can simultaneously optimize the geometry and the mass of structures. We present the details of our technique together with examples illustrating its use, including comparisons with real structures.
17174080
A memetic algorithm to schedule planned maintenance for the national grid
The combination of local search operators, problem specific information and a genetic algorithm has provided very good results in certain scheduling problems, particularly in timetabling and maintenance scheduling problems. The resulting algorithm from this hybrid approach has been termed a Memetic Algorithm. This paper investigates the use of such an algorithm for the scheduling of transmission line maintenance for a known problem that has been addressed in the literature using a combination of a genetic algorithm and greedy optimisers.This problem is concerned with the scheduling of maintenance for an electricity transmission network where every transmission line must be maintained once within a specified time period. The objective is to avoid situations where sections of the network are disconnected, and to minimise the overloading of lines which are in service.In this paper we look at scheduling maintenance for the South Wales region of the national transmission network. We present and discuss, in some detail, a memetic algorithm that incorporates local search operators including tabu search and simulated annealing. A comparison is made both with the results from previous work, and against a selection of optimising techniques.The approach presented in this paper shows a significant improvement over previously published results on previously tackled problems. We also present results on another problem which has not been tackled in the literature but which is closer to the real world maintenance scheduling problems faced by such companies as The National Grid Company plc using the South Wales region.
5097884
Columbia Digital News System. An environment for briefing and search over multimedia information
In this paper we describe an ongoing research project called the Columbia Digital News System. The goal of this project is to develop a suite of effective interoperable tools with which people can find relevant information (text, images, video, and structured documents) from distributed sources and track it over a period of time. Our initial focus is on the development of a system with which researchers, journalists, and students can keep track of current news events in specific areas.
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.