A parallel version of Polyflow

1995 ◽  
pp. 826-830
Author(s):  
F. Debae ◽  
Y. Jiang ◽  
J. M. Marchal ◽  
P. Henriksen
Keyword(s):  
Parallel Version

Exploiting Soft Constraints within Decomposition and Coordination Methods for Sub-hourly Unit Commitment

2020 ◽  
Author(s):  
Niranjan Raghunathan ◽  
Mikhail Bragin ◽  
Bing Yan ◽  
Peter Luh ◽  
Khosrow Moslehi ◽  
...  
Keyword(s):  
Unit Commitment ◽  
Daily Basis ◽  
Time Limit ◽  
Soft Constraints ◽  
Problem Complexity ◽  
Surrogate Optimization ◽  
Parallel Version ◽  
Improved Performance ◽  
Coordination Methods ◽  
Relaxed Problem

Unit commitment (UC) is an important problem solved on a daily basis within a strict time limit. While hourly UC problems are currently considered, they may not be flexible enough with the fast-changing demand and the increased penetration of intermittent renewables. Sub-hourly UC is therefore recommended. This, however, will significantly increase problem complexity even under the deterministic setting, and current methods may not be able to obtain good solutions within the time limit. In this paper, deterministic sub-hourly UC is considered, with the innovative exploitation of soft constraints – constraints that do not need to be strictly satisfied, but with predetermined penalty coefficients for their violations. The key idea is the “surrogate optimization” concept that ensures multiplier convergence within “surrogate” Lagrangian relaxation as long as the “surrogate optimality condition” is satisfied without the need to optimally solve the “relaxed problem.” Consequently, subproblems can still be formed and optimized when soft constraints are not relaxed, leading to a drastically reduced number of multipliers and improved performance. To further enhance the method, a parallel version is developed. Testing results on the Polish system demonstrate the effectiveness and robustness of both the sequential and parallel versions at finding high-quality solutions within the time limit.

Parallel Version of the Framework for Clustering Error Messages

2021 ◽  
Vol 42 (7) ◽  
pp. 1596-1607
Author(s):  
M. Vorobyov ◽  
K. Zhukov ◽  
M. Grigorieva ◽  
S. Korobkov
Keyword(s):  
Parallel Version

A parallel version of FORM 3

2001 ◽  
Author(s):  
D. Fliegner
Keyword(s):  
Parallel Version

scholarly journals SEQUENTIAL AND PARALLEL ALGORITHMS FOR THE k CLOSEST PAIRS PROBLEM

1995 ◽  
Vol 05 (03) ◽  
pp. 273-288 ◽  
Author(s):  
HANS-PETER LENHOF ◽  
MICHIEL SMID
Keyword(s):  
Decision Tree ◽  
Parallel Algorithms ◽  
Dimensional Space ◽  
Decision Tree Model ◽  
Sequential Algorithm ◽  
Tree Model ◽  
Parallel Time ◽  
Parallel Version ◽  
Pram Model ◽  
Crcw Pram

Let S be a set of n points in D-dimensional space, where D is a constant, and let k be an integer between 1 and [Formula: see text]. A new and simpler proof is given of Salowe’s theorem, i.e., a sequential algorithm is given that computes the k closest pairs in the set S in O(n log n+k) time, using O(n+k) space. The algorithm fits in the algebraic decision tree model and is, therefore, optimal. Salowe’s algorithm seems difficult to parallelize. A parallel version of our algorithm is given for the CRCW-PRAM model. This version runs in O((log n)2 log log n) expected parallel time and has an O(n log n log log n+k) time-processor product. Finally, actual running times are given of an implementation of our sequential algorithm.

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