An efficient algorithm for the multi-state two separate minimal paths reliability problem with budget constraint

2015 ◽  
Vol 142 ◽  
pp. 472-481 ◽  
Author(s):  
Majid Forghani-elahabad ◽  
Nezam Mahdavi-Amiri
Keyword(s):  
Efficient Algorithm ◽  
Budget Constraint ◽  
Reliability Problem ◽  
Minimal Paths

SYSTEM RELIABILITY OF A STOCHASTIC-FLOW NETWORK WITH NODES HAVING CAPACITY AND COST ATTRIBUTES

2006 ◽  
Vol 13 (03) ◽  
pp. 203-212 ◽  
Author(s):  
YI-KUEI LIN
Keyword(s):  
System Reliability ◽  
Efficient Algorithm ◽  
Maximum Flow ◽  
Budget Constraint ◽  
Stochastic Flow ◽  
Minimal Path ◽  
Flow Network ◽  
Minimal Paths ◽  
Order Sequence

A stochastic-flow network in which nodes as well as arcs all have both capacity and cost attributes is studied. We evaluate the possibility that the maximum flow of the network is not less than a demand under the budget constraint. Such a possibility is in general called the system reliability. A minimal path, an order sequence of arcs & nodes from the source to the sink without cycles, is used to assign the flow to each component (arc or node). Based on minimal paths, an efficient algorithm is proposed to generate all (d, C)-MPs that are the minimal capacity vectors meeting the demand d and the budget C. The system reliability can then be calculated in terms of all (d, C)-MPs.

On multi-state two separate minimal paths reliability problem with time and budget constraints

2020 ◽  
Vol 37 (4) ◽  
pp. 479
Author(s):  
Majid Forghani Elahabad ◽  
Nezam Mahdavi Amiri ◽  
Nelson Kagan
Keyword(s):  
Budget Constraints ◽  
Reliability Problem ◽  
Minimal Paths

Computational Micrograph Registration with Sieve Processes

1996 ◽  
Vol 54 ◽  
pp. 440-441
Author(s):  
P.J. Phillips ◽  
J. Huang ◽  
S. M. Dunn
Keyword(s):  
Planar Graph ◽  
Efficient Algorithm ◽  
Spatial Organization ◽  
Spatial Arrangement ◽  
Stereo Image ◽  
Image Model ◽  
Geometric Invariants ◽  
Point Set

In this paper we present an efficient algorithm for automatically finding the correspondence between pairs of stereo micrographs, the key step in forming a stereo image. The computation burden in this problem is solving for the optimal mapping and transformation between the two micrographs. In this paper, we present a sieve algorithm for efficiently estimating the transformation and correspondence.In a sieve algorithm, a sequence of stages gradually reduce the number of transformations and correspondences that need to be examined, i.e., the analogy of sieving through the set of mappings with gradually finer meshes until the answer is found. The set of sieves is derived from an image model, here a planar graph that encodes the spatial organization of the features. In the sieve algorithm, the graph represents the spatial arrangement of objects in the image. The algorithm for finding the correspondence restricts its attention to the graph, with the correspondence being found by a combination of graph matchings, point set matching and geometric invariants.

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