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Everything about Johnson's algorithm
Method to find shortest paths
Johnson's algorithm is a way to find the shortest paths between all pairs of vertices in an edge-weighted directed graph. It allows some of the edge weights to be negative numbers, but no negative-weight cycles may exist. It works by using the Bellman–Ford algorithm to compute a transformation of the input graph that removes all negative weights, allowing Dijkstra's algorithm to be used on the transformed graph. It is named after Donald B. Johnson, who first published the technique in 1977. Wikipedia →
🧭 Start here: a 6-step reading path
- Read the overview: Johnson's algorithmA 5-minute orientation
- Skim a recent paper: A simple and fast algorithm for computing discrete Voronoi, Johnson-Mehl or Laguerre diagrams of pointsInfluential work since 2022
- Pick up a classic book: A model-based approach for the measurement of eye movements using image processingThe most-reprinted book on the subject
- Read the landmark paper: Algorithm AS 99: Fitting Johnson Curves by MomentsCited 234 times
- Go sideways: Suurballe's algorithmA closely related topic
- Go sideways: Dijkstra's algorithmA closely related topic
📖 Definitions
No dictionary entry for this exact phrase.
🗂️ The subject at a glance
🏆 Landmark papers (most cited)
Algorithm AS 99: Fitting Johnson Curves by Moments
Implementing the Dantzig-Fulkerson-Johnson algorithm for large traveling salesman problems
Algorithm AS 100: Normal-Johnson and Johnson-Normal Transformations
A new triangular fuzzy Johnson algorithm
The Ford-Johnson Sorting Algorithm Is Not Optimal
An Algorithm for Fitting Johnson Transformations to Non-Normal Data
The Ford–Johnson algorithm still unbeaten for less than 47 elements
Ancova—A One Covariate Johnson-Neyman Algorithm
🆕 Influential since 2022
A simple and fast algorithm for computing discrete Voronoi, Johnson-Mehl or Laguerre diagrams of points
Optimal prediction and validation of Johnson-Cook failure model for Al 6061 using genetic algorithm
Optimal Calibration of Q235B Steel Johnson-Cook Model Parameters Based on Global Response Surface Algorithm
Estimation Method for Non-acoustic Parameters of the Johnson-Champoux-Allard Model using Genetic Algorithm
Genetic algorithm–based calibration of the Johnson–Cook fracture model for high strain rate conditions
📚 Books worth reading
- 📕A model-based approach for the measurement of eye movements using image processingKwangjae Sung · 1997
Practical Electronics for InventorsPaul Scherz · 2000
Handbook of Theoretical Computer ScienceJan van Leeuwen · 1990- 📕An analytical model for footprint dispersions and its application to mission designJ. R. Jagannatha Rao · 1992
Computational Linguistics and Formal Semantics (Studies in Natural Language Processing)Michael Rosner · 1992
The traveling salesman problem and its variationsGregory Gutin · 2002
Abstract machine models for parallel and distributed computingM. Kara · 1996
Handbook of biosurveillanceAndrew W. Moore · 2006
Ranked by number of editions on Open Library, a rough measure of how lasting a book is.
🔗 Related topics
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