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Hierarchical encoded path views for path query processing: An optimal model and its performance evaluation
 IEEE Transactions on Knowledge and Data Engineering
, 1998
"... Abstract—Efficient path computation is essential for applications such as intelligent transportation systems (ITS) and network routing. In ITS navigation systems, many path requests can be submitted over the same, typically huge, transportation network within a small time window. While path precompu ..."
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Cited by 69 (2 self)
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Abstract—Efficient path computation is essential for applications such as intelligent transportation systems (ITS) and network routing. In ITS navigation systems, many path requests can be submitted over the same, typically huge, transportation network within a small time window. While path precomputation (path view) would provide an efficient path query response, it raises three problems which must be addressed: 1) precomputed paths exceed the current computer main memory capacity for large networks; 2) diskbased solutions are too inefficient to meet the stringent requirements of these target applications; and 3) path views become too costly to update for large graphs (resulting in outofdate query results). We propose a hierarchical encoded path view (HEPV) model that addresses all three problems. By hierarchically encoding partial paths, HEPV reduces the view encoding time, updating time and storage requirements beyond previously known path precomputation techniques, while significantly minimizing path retrieval time. We prove that paths retrieved over HEPV are optimal. We present complete solutions for all phases of the HEPV approach, including graph partitioning, hierarchy generation, path view encoding and updating, and path retrieval. In this paper, we also present an indepth experimental evaluation of HEPV based on both synthetic and real GIS networks. Our results confirm that HEPV offers advantages over alternative path finding approaches in terms of performance and space efficiency. Index Terms—Path queries, path view materialization, hierarchical path search, GIS databases, graph partitioning. 1
Applications of Modern Heuristic Search Methods to Pattern Sequencing Problems
 COMPUTERS & OPERATIONS RESEARCH
, 1999
"... This article describes applications of modern heuristic search methods to pattern sequencing problems, i.e., problems seeking for a permutation of the rows of a given matrix with respect to some given objective function. We consider two di#erent objectives: Minimization of the number of simultane ..."
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Cited by 21 (6 self)
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This article describes applications of modern heuristic search methods to pattern sequencing problems, i.e., problems seeking for a permutation of the rows of a given matrix with respect to some given objective function. We consider two di#erent objectives: Minimization of the number of simultaneously open stacks and minimization of the average order spread. Both objectives require the adaptive evaluation of changed solutions to allow an e#cient application of neighbourhood search techniques.
The history of the cluster heat map
 The American Statistician
, 2009
"... The cluster heat map is an ingenious display that simultaneously reveals row and column hierarchical cluster structure in a data matrix. It consists of a rectangular tiling with each tile shaded on a color scale to represent the value of the corresponding element of the data matrix. The rows (column ..."
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Cited by 16 (0 self)
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The cluster heat map is an ingenious display that simultaneously reveals row and column hierarchical cluster structure in a data matrix. It consists of a rectangular tiling with each tile shaded on a color scale to represent the value of the corresponding element of the data matrix. The rows (columns) of the tiling are ordered such that similar rows (columns) are near each other. On the vertical and horizontal margins of the tiling there are hierarchical cluster trees. This cluster heat map is a synthesis of several different graphic displays developed by statisticians over more than a century. We locate the earliest sources of this display in late 19th century publications. And we trace a diverse 20th century statistical literature that provided a foundation for this most widely used of all bioinformatics displays. 1
BioMed Central
, 2006
"... A novel approach to phylogenetic tree construction using stochastic optimization and clustering ..."
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Cited by 4 (2 self)
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A novel approach to phylogenetic tree construction using stochastic optimization and clustering
Constructive Genetic Algorithm for MachinePart Cell Formation
, 2000
"... This paper presents a new evolutionary approach to the machinepart cell formation (MPCF) problem, generally considered in manufacturing cell design, where a zeroone machinepart matrix must have its rows and columns moved to form machines and parts clusters. The Constructive Genetic Algorithm (CGA ..."
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Cited by 1 (1 self)
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This paper presents a new evolutionary approach to the machinepart cell formation (MPCF) problem, generally considered in manufacturing cell design, where a zeroone machinepart matrix must have its rows and columns moved to form machines and parts clusters. The Constructive Genetic Algorithm (CGA) was proposed recently to solve clustering problems, and is applied here to the MPCF. The MPCF is modeled as a biobjective problem that guides the construction of feasible assignments of machines and parts to specify clusters, and provides evaluation of schemata and structures in a common basis. A particularly derived structure and schema representation considers Jaccard distances for binary strings. A variable size population is formed only by schemata, considered as building blocks for feasible solutions construction along the generations. Recombination gives population diversification, and local search mutation is applied to structures that represent feasible solutions. Experimental res...
Vertical partitioning of relational OLTP databases using integer programming
"... Abstract — A way to optimize performance of relational row store databases is to reduce the row widths by vertically partitioning tables into table fractions in order to minimize the number of irrelevant columns/attributes read by each transaction. This paper considers vertical partitioning algorith ..."
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Abstract — A way to optimize performance of relational row store databases is to reduce the row widths by vertically partitioning tables into table fractions in order to minimize the number of irrelevant columns/attributes read by each transaction. This paper considers vertical partitioning algorithms for relational rowstore OLTP databases with an Hstorelike architecture, meaning that we would like to maximize the number of singlesited transactions. We present a model for the vertical partitioning problem that, given a schema together with a vertical partitioning and a workload, estimates the costs (bytes read/written by storage layer access methods and bytes transferred between sites) of evaluating the workload on the given partitioning. The cost model allows for arbitrarily prioritizing load balancing of sites vs. total cost minimization. We show that finding a minimumcost vertical partitioning in this model is NPhard and therefore the problem should obviously not be solved manually by a human DBA. We present two algorithms returning solutions in which singlesitedness of read queries is preserved while allowing column replication (which may allow a drastically reduced cost compared to disjoint partitioning). The first algorithm is a quadratic integer program that finds optimal minimumcost solutions with respect to the model, and the second algorithm is a more scalable heuristic based on simulated annealing. Experiments show that the algorithms can reduce the cost of the model objective by 37 % when applied to the TPCC benchmark and the heuristic is shown to obtain solutions with costs close to the ones found using the quadratic program. I.
Annals of Operations Research 65(1996)3554 35 Manufacturing cell formation by statespace search*
"... This paper addresses the problem of grouping machines in order to design cellular manufacturing ceils, with an objective to minimize intercell flow. This problem is related to one of the major aims of group technology (GT): to decompose the manufacturing system into manufacturing cells that are as ..."
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This paper addresses the problem of grouping machines in order to design cellular manufacturing ceils, with an objective to minimize intercell flow. This problem is related to one of the major aims of group technology (GT): to decompose the manufacturing system into manufacturing cells that are as independent as possible. This problem is NPhard. Thus, nonheuristic methods cannot address problems of typical industrial dimensions because they would require exorbitant amounts of computing time, while fast heuristic methods may suffer from poor solution quality. We present a branchandbound statespace search algorithm that attempts to overcome both these deficiencies. One of the major strengths of this algorithm is its efficient branching and search strategy. In addition, the algorithm employs the fast InterCell Traffic Minimization Method to provide good upper bounds, and computes lower bounds based on a relaxation of merging.
A Comparison of Knives for Bread Slicing
"... Vertical partitioning is a crucial step in physical database design in roworiented databases. A number of vertical partitioning algorithms have been proposed over the last three decades for a variety of niche scenarios. In principle, the underlying problem remains the same: decompose a table into o ..."
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Vertical partitioning is a crucial step in physical database design in roworiented databases. A number of vertical partitioning algorithms have been proposed over the last three decades for a variety of niche scenarios. In principle, the underlying problem remains the same: decompose a table into one or more vertical partitions. However, it is not clear how good different vertical partitioning algorithms are in comparison to each other. In fact, it is not even clear how to experimentally compare different vertical partitioning algorithms. In this paper, we present an exhaustive experimental study of several vertical partitioning algorithms. We categorize vertical partitioning algorithms along three dimensions. We survey six vertical partitioning algorithms and discuss their pros and cons. We identify the major differences in the usecase settings for different algorithms and describe how to make an applestoapples comparison of different vertical partitioning algorithms under the same setting. We propose four metrics to compare vertical partitioning algorithms. We show experimental results from the TPCH and SSB benchmark and present four key lessons learned: (1) we can do four orders of magnitude less computation and still find the optimal layouts, (2) the benefits of vertical partitioning depend strongly on the database buffer size, (3) HillClimb is the best vertical partitioning algorithm, and (4) vertical partitioning for TPCHlike benchmarks can improve over column layout by only up to 5%.