• Documents
  • Authors
  • Tables
  • Log in
  • Sign up
  • MetaCart
  • DMCA
  • Donate

CiteSeerX logo

Advanced Search Include Citations

Tools

Sorted by:
Try your query at:
Semantic Scholar Scholar Academic
Google Bing DBLP
Results 1 - 10 of 9,263
Next 10 →

SUBMITTED TO THE IEEE TRANSACTIONS ON ROBOTICS 1 Iterative MILP Methods for Vehicle Control Problems

by Matthew G. Earl
"... Abstract Mixed integer linear programming (MILP) is a powerful tool for planning and control problems because of its modeling capability and the availability of good solvers. However, for large models, MILP methods suffer computationally. In this paper, we present iterative MILP algorithms that add ..."
Abstract - Add to MetaCart
that address this issue. We consider trajectory generation problems with obstacle avoidance requirements and minimum time trajectory generation problems. The algorithms use fewer binary variables than standard MILP methods and require less computational effort. I.

Iterative MILP methods for vehicle-control problems

by Matthew G. Earl, Senior Member - IEEE Transactions on Robotics
"... Abstract—Mixed-integer linear programming (MILP) is a powerful tool for planning and control problems because of its modeling capability and the availability of good solvers. However, for large models, MILP methods suffer computationally. In this paper, we present iterative MILP algorithms that addr ..."
Abstract - Cited by 20 (0 self) - Add to MetaCart
that address this issue. We consider trajectory-generation problems with obstacle-avoidance requirements and minimum-time trajectory-generation problems. These problems involve vehicles that are described by mixed logical dynamical equations, a form of hybrid system. The algorithms use fewer binary variables

Minimum-Time Control of Systems With Coloumb Friction: Near Global Optima Via Mixed Integer "L inear Programming'

by Brian J Driessen , Nader Sadegh
"... Abstract: This work presents a method of finding near global optima to minimum-time trajectory generation problem for systems that would be linear if it were not for the presence of Coloumb friction. The required final state of the system is assumed to be maintainable by the system, and the input b ..."
Abstract - Add to MetaCart
Abstract: This work presents a method of finding near global optima to minimum-time trajectory generation problem for systems that would be linear if it were not for the presence of Coloumb friction. The required final state of the system is assumed to be maintainable by the system, and the input

Scheduling Multithreaded Computations by Work Stealing

by Robert D. Blumofe , Charles E. Leiserson , 1994
"... This paper studies the problem of efficiently scheduling fully strict (i.e., well-structured) multithreaded computations on parallel computers. A popular and practical method of scheduling this kind of dynamic MIMD-style computation is “work stealing," in which processors needing work steal com ..."
Abstract - Cited by 568 (34 self) - Add to MetaCart
is Tp = O(TI/P + Tm), where TI is the minimum serial eze-cution time of the multithreaded computation and T, is the minimum ezecution time with an infinite number of processors. Moreover, the space Sp required by the execution satisfies Sp 5 SIP. We also show that the ezpected total communication

How bad is selfish routing?

by Tim Roughgarden, Éva Tardos - JOURNAL OF THE ACM , 2002
"... We consider the problem of routing traffic to optimize the performance of a congested network. We are given a network, a rate of traffic between each pair of nodes, and a latency function for each edge specifying the time needed to traverse the edge given its congestion; the objective is to route t ..."
Abstract - Cited by 657 (27 self) - Add to MetaCart
We consider the problem of routing traffic to optimize the performance of a congested network. We are given a network, a rate of traffic between each pair of nodes, and a latency function for each edge specifying the time needed to traverse the edge given its congestion; the objective is to route

Fibonacci Heaps and Their Uses in Improved Network optimization algorithms

by Michael L. Fredman, Robert Endre Tarjan , 1987
"... In this paper we develop a new data structure for implementing heaps (priority queues). Our structure, Fibonacci heaps (abbreviated F-heaps), extends the binomial queues proposed by Vuillemin and studied further by Brown. F-heaps support arbitrary deletion from an n-item heap in qlogn) amortized tim ..."
Abstract - Cited by 739 (18 self) - Add to MetaCart
matching), improved from O(nm log0dn+2)n); (4) O(mj3(m, n)) for the minimum spanning tree problem, improved from O(mloglo&,,.+2,n), where j3(m, n) = min {i 1 log % 5 m/n). Note that B(m, n) 5 log*n if m 2 n. Of these results, the improved bound for minimum spanning trees is the most striking, although

Mining Sequential Patterns: Generalizations and Performance Improvements

by Ramakrishnan Srikant, Rakesh Agrawal - RESEARCH REPORT RJ 9994, IBM ALMADEN RESEARCH , 1995
"... The problem of mining sequential patterns was recently introduced in [3]. We are given a database of sequences, where each sequence is a list of transactions ordered by transaction-time, and each transaction is a set of items. The problem is to discover all sequential patterns with a user-specified ..."
Abstract - Cited by 759 (5 self) - Add to MetaCart
generalize the problem as follows. First, we add time constraints that specify a minimum and/or maximum time period between adjacent elements in a pattern. Second, we relax the restriction that the items in an element of a sequential pattern must come from the same transaction, instead allowing the items

Mining Sequential Patterns

by Rakesh Agrawal, Ramakrishnan Srikant , 1995
"... We are given a large database of customer transactions, where each transaction consists of customer-id, transaction time, and the items bought in the transaction. We introduce the problem of mining sequential patterns over such databases. We present three algorithms to solve this problem, and empiri ..."
Abstract - Cited by 1568 (6 self) - Add to MetaCart
We are given a large database of customer transactions, where each transaction consists of customer-id, transaction time, and the items bought in the transaction. We introduce the problem of mining sequential patterns over such databases. We present three algorithms to solve this problem

A general approximation technique for constrained forest problems

by Michel X. Goemans, David P. Williamson - SIAM J. COMPUT. , 1995
"... We present a general approximation technique for a large class of graph problems. Our technique mostly applies to problems of covering, at minimum cost, the vertices of a graph with trees, cycles, or paths satisfying certain requirements. In particular, many basic combinatorial optimization proble ..."
Abstract - Cited by 414 (21 self) - Add to MetaCart
problems fit in this framework, including the shortest path, minimum-cost spanning tree, minimum-weight perfect matching, traveling salesman, and Steiner tree problems. Our technique produces approximation algorithms that run in O(n log n) time and come within a factor of 2 of optimal for most

Simple fast algorithms for the editing distance between trees and related problems

by Kaizhong Zhang, Dennis Shasha - SIAM J. COMPUT , 1989
"... Ordered labeled trees are trees in which the left-to-right order among siblings is. significant. The distance between two ordered trees is considered to be the weighted number of edit operations (insert, delete, and modify) to transform one tree to another. The problem of approximate tree matching i ..."
Abstract - Cited by 405 (12 self) - Add to MetaCart
Ordered labeled trees are trees in which the left-to-right order among siblings is. significant. The distance between two ordered trees is considered to be the weighted number of edit operations (insert, delete, and modify) to transform one tree to another. The problem of approximate tree matching
Next 10 →
Results 1 - 10 of 9,263
Powered by: Apache Solr
  • About CiteSeerX
  • Submit and Index Documents
  • Privacy Policy
  • Help
  • Data
  • Source
  • Contact Us

Developed at and hosted by The College of Information Sciences and Technology

© 2007-2019 The Pennsylvania State University