An Approximate Dynamic Programming Algorithm for Large-Scale Fleet Management: A Case Application

2009 ◽  
Vol 43 (2) ◽  
pp. 178-197 ◽  
Author(s):  
Hugo P. Simão ◽  
Jeff Day ◽  
Abraham P. George ◽  
Ted Gifford ◽  
John Nienow ◽  
...  
Keyword(s):  
Dynamic Programming ◽  
Large Scale ◽  
Approximate Dynamic Programming ◽  
Dynamic Programming Algorithm ◽  
Programming Algorithm ◽  
Fleet Management ◽  
Case Application

Multidimensional Parallel Dynamic Programming Algorithm Based on Spark for Large-Scale Hydropower Systems

2020 ◽  
Vol 34 (11) ◽  
pp. 3427-3444 ◽  
Author(s):  
Yufei Ma ◽  
Ping-an Zhong ◽  
Bin Xu ◽  
Feilin Zhu ◽  
Yao Xiao ◽  
...  
Keyword(s):  
Dynamic Programming ◽  
Large Scale ◽  
Dynamic Programming Algorithm ◽  
Programming Algorithm

scholarly journals On the 2-MRS Problem in a Tree with Unreliable Edges

2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
Wei Ding ◽  
Yu Zhou ◽  
Guangting Chen ◽  
Hongfa Wang ◽  
Guangming Wang
Keyword(s):  
Dynamic Programming ◽  
Communication Networks ◽  
Large Scale ◽  
Dynamic Programming Algorithm ◽  
Programming Algorithm ◽  
Probability Models ◽  
Expected Number ◽  
Node Pair ◽  
Reliable Source ◽  
General Graphs

This paper extends the well-known most reliable source (1-MRS) problem in unreliable graphs to the 2-most reliable source (2-MRS) problem. Two kinds of reachable probability models of node pair in unreliable graphs are considered, that is, the superior probability and united probability. The 2-MRS problem aims to find a node pair in the graph from which the expected number of reachable nodes or the minimum reachability is maximized. It has many important applications in large-scale unreliable computer or communication networks. The #P-hardness of the 2-MRS problem in general graphs follows directly from that of the 1-MRS problem. This paper deals with four models of the 2-MRS problem in unreliable trees where every edge has an independent working probability and devises a cubic-time and quadratic-space dynamic programming algorithm, respectively, for each model.

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