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27
New DistanceDirected Algorithms for Maximum Flow and Parametric Maximum Flow Problems
, 1987
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Experimental evaluation of parametric maxflow algorithms
 In WEA ’07: Proceedings of the 6th Workshop on Experimental Algorithms
, 2007
"... Abstract. The parametric maximum flow problem is an extension of the classical maximum flow problem in which the capacities of certain arcs are not fixed but are functions of a single parameter. Gallo et al. [6] showed that certain versions of the pushrelabel algorithm for ordinary maximum flow can ..."
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Abstract. The parametric maximum flow problem is an extension of the classical maximum flow problem in which the capacities of certain arcs are not fixed but are functions of a single parameter. Gallo et al. [6] showed that certain versions of the pushrelabel algorithm for ordinary maximum flow can be extended to the parametric problem while only increasing the worstcase time bound by a constant factor. Recently Zhang et al. [14,13] proposed a novel, simple balancing algorithm for the parametric problem on bipartite networks. They claimed good performance for their algorithm on networks arising from a realworld application. We describe the results of an experimental study comparing the performance of the balancing algorithm, the GGT algorithm, and a simplified version of the GGT algorithm, on networks related to those of the application of Zhang et al. as well as networks designed to be hard for the balancing algorithm. Our implementation of the balancing algorithm beats both versions of the GGT algorithm on networks related to the application, thus supporting the observations of Zhang et al. On the other hand, the GGT algorithm is more robust; it beats the balancing algorithm on some natural networks, and by asymptotically increasing amount on networks designed to be hard for the balancing algorithm. 1
Algorithms for Joint Optimization of Stability and Diversity in Planning Combinatorial Libraries of Chimeric Proteins
"... Abstract. In engineering protein variants by constructing and screening combinatorial libraries of chimeric proteins, two complementary and competing goals are desired: the new proteins must be similar enough to the evolutionarilyselected wildtype proteins to be stably folded, and they must be dif ..."
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Abstract. In engineering protein variants by constructing and screening combinatorial libraries of chimeric proteins, two complementary and competing goals are desired: the new proteins must be similar enough to the evolutionarilyselected wildtype proteins to be stably folded, and they must be different enough to display functional variation. We present here the first method, Staversity, to simultaneously optimize stability and diversity in selecting sets of breakpoint locations for sitedirected recombination. Our goal is to uncover all “undominated ” breakpoint sets, for which no other breakpoint set is better in both factors. Our first algorithm finds the undominated sets serving as the vertices of the lower envelope of the twodimensional (stability and diversity) convex hull containing all possible breakpoint sets. Our second algorithm identifies additional breakpoint sets in the concavities that are either undominated or dominated only by undiscovered breakpoint sets within a distance bound computed by the algorithm. Both algorithms are efficient, requiring only
Algorithmic techniques for geometric optimization
 In Computer Science Today: Recent Trends and Developments, Lecture Notes in Computer Science
, 1995
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Distancedirected augmenting path algorithms for maximum flow and parametric maximum flow problems
 Naval Research Logistics
, 1991
"... Until recently, fast algorithms for the maximum flow problem have typically proceeded by constructing layered networks and establishing blocking flows in these networks. However, in recent years, new distancedirected algorithms have been suggested that do not construct layered networks but instead ..."
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Until recently, fast algorithms for the maximum flow problem have typically proceeded by constructing layered networks and establishing blocking flows in these networks. However, in recent years, new distancedirected algorithms have been suggested that do not construct layered networks but instead maintain a distance label with each node. The distance label of a node is a lower bound on the length of the shortest augmenting path from the node to the sink. In this article we develop two distancedirected augmenting path algorithms for the maximum flow problem. Both the algorithms run in O(n 2 m) time on networks with n nodes and m arcs. We also point out the relationship between the distance labels and layered networks. Using a scaling technique, we improve the complexity of our distancedirected algorithms to O(nm log U), where U denotes the largest arc capacity. We also consider applications of these algorithms to unit capacity maximum flow problems and a class of parametric maximum flow problems. t i
Balancing applied to maximum network flow problems
 In Proc. ESA, LNCS 4168
, 2006
"... Abstract. We explore balancing as a definitional and algorithmic tool for finding minimum cuts and maximum flows in ordinary and parametric networks. We show that a standard monotonic parametric maximum flow problem can be formulated as a problem of computing a particular maximum flow that is balanc ..."
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Abstract. We explore balancing as a definitional and algorithmic tool for finding minimum cuts and maximum flows in ordinary and parametric networks. We show that a standard monotonic parametric maximum flow problem can be formulated as a problem of computing a particular maximum flow that is balanced in an appropriate sense. We present a divideandconquer algorithm to compute such a balanced flow in a logarithmic number of ordinary maximumflow computations. For the special case of a bipartite network, we present two simple, local algorithms for computing a balanced flow. The local balancing idea becomes even simpler when applied to the ordinary maximum flow problem. For this problem, we present a roundrobin arcbalancing algorithm that computes a maximum flow on an nvertex, marc network with integer arc capacities of at most U in O(n 2 mlog(nU)) time. Although this algorithm is slower by at least a factor of n than other known algorithms, it is extremely simple and wellsuited to parallel and distributed implementation. 1
On the Calculation of the Stability Radius of an Optimal or an Approximate Schedule
 Eq. Class i) (Eq. Class ii) (Eq. Class iii) (Eq. Class iv) (Eq. Class v) (Eq. Class vi) (Eq. Class viii) (Eq. Class vii) (Eq. Class ix
, 1998
"... : The main objective of this paper is to stimulate interest in stability analysis for scheduling problems. In spite of impressive theoretical results in sequencing and scheduling, up to now the implementation of scheduling algorithms with a rather deep mathematical background in production planning, ..."
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: The main objective of this paper is to stimulate interest in stability analysis for scheduling problems. In spite of impressive theoretical results in sequencing and scheduling, up to now the implementation of scheduling algorithms with a rather deep mathematical background in production planning, scheduling and control, and in other reallife problems with sequencing aspects is limited. In classical scheduling theory, mainly deterministic systems are considered and the processing times of all operations are supposed to be given in advance. Such problems do not often arise in practice: Even if the processing times are known before applying a scheduling procedure, OR workers are forced to take into account the precision of equipment, which is used to calculate the processing times, roundoff errors in the calculation of a schedule, errors within the practical realization of a schedule, machine breakdowns, additional jobs and so on. This paper is devoted to the calculation of the stabi...
Approximating the Minimum Chain Completion problem
"... A bipartite graph G = (U, V, E) is a chain graph [9] if there is a bijection π: {1,..., U} → U such that Γ (π (1)) ⊇ Γ (π (2)) ⊇... ⊇ Γ (π (U)), where Γ is a function that maps a node to its neighbors. We give approximation algorithms for two variants of the Minimum Chain Completion problem, ..."
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A bipartite graph G = (U, V, E) is a chain graph [9] if there is a bijection π: {1,..., U} → U such that Γ (π (1)) ⊇ Γ (π (2)) ⊇... ⊇ Γ (π (U)), where Γ is a function that maps a node to its neighbors. We give approximation algorithms for two variants of the Minimum Chain Completion problem, where we are given a bipartite graph G(U, V, E), and the goal is find the minimum set of edges F that need to be added to G such that the bipartite graph G ′ = (U, V, E ′ ) (E ′ = E ∪ F) is a chain graph. 1
Vertical partitioning impact on performance and manageability of distributed database systems (A Comparative study of some vertical partitioning algorithms)
 18TH NATIONAL COMPUTER CONFERENCE
, 2006
"... Users of distributed database systems often observe performance problems such as unexpectedly low throughput or high latency. Determining the cause of the performance problems can be very hard task. Bottlenecks can occur in any of the components through which the data flows: the applications, the op ..."
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Users of distributed database systems often observe performance problems such as unexpectedly low throughput or high latency. Determining the cause of the performance problems can be very hard task. Bottlenecks can occur in any of the components through which the data flows: the applications, the operating systems, the network interfaces and hardware. Horizontal and vertical partitioning are important aspects of physical design in relational database system that has a significant impact on performance. The distribution design involves making decisions on the fragmentation and the allocation of data across the sites of a computer network. In this paper we address the fragmentation phase of distributed database systems. In this paper, vertical partitioning problem during the design of distributed databases is discussed by conducting a comparative study for different vertical partitioning algorithms to reach the most efficient vertical fragmentation scheme that leads to a proper data allocation and replication.