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A comparison of two algorithms for the assignment problem

https://doi.org/10.1007/bf01299157
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/net.3230010206openalex-snapshot
On some techniques useful for solution of transportation network problems
inferredcites →https://doi.org/10.1002/net.3230100205openalex-snapshot
An algorithm to solve the m × n assignment problem in expected time O(mn log n)
inferredcites →https://doi.org/10.1007/bf01584237openalex-snapshot
A new algorithm for the assignment problem
inferredcites →https://doi.org/10.1007/bf01589405openalex-snapshot
Dual coordinate step methods for linear network flow problems
inferredcites →https://doi.org/10.1007/bf02022037openalex-snapshot
The shortest augmenting path method for solving assignment problems — Motivation and computational experience
inferredcites →https://doi.org/10.1007/bf02186476openalex-snapshot
The auction algorithm: A distributed relaxation method for the assignment problem
inferredcites →https://doi.org/10.1007/bf02278710openalex-snapshot
A shortest augmenting path algorithm for dense and sparse linear assignment problems
inferredcites →https://doi.org/10.1057/jors.1990.157openalex-snapshot
Handbooks in Operations Research and Management Science, Volume 1 -- Optimization
inferredcites →https://doi.org/10.1145/321694.321699openalex-snapshot
Theoretical Improvements in Algorithmic Efficiency for Network Flow Problems
inferredcites →https://doi.org/10.1287/ijoc.3.2.92openalex-snapshot
Performance Characteristics of the Jacobi and the Gauss-Seidel Versions of the Auction Algorithm on the Alliant FX/8
inferredcites →https://doi.org/10.1287/ijoc.3.4.299openalex-snapshot
An Empirical Analysis of the Dense Assignment Problem: Sequential and Parallel Implementations
inferredcites →https://doi.org/10.21236/ada233588openalex-snapshot
A Parallel Shortest Augmenting Path Algorithm for the Assignment Problem

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1007/978-1-4613-3400-2_6openalex-snapshot
Parallel Algorithms for Network Problems
inferred← citeshttps://doi.org/10.1007/978-1-4757-3023-4_2openalex-snapshot
Linear Assignment Problems and Extensions
inferred← citeshttps://doi.org/10.1007/bf01299446openalex-snapshot
Data parallel computing for network-structured optimization problems
inferred← citeshttps://doi.org/10.1007/bf02684400openalex-snapshot
Massively parallel augmenting path algorithms for the assignment problem
inferred← citeshttps://doi.org/10.1007/s10479-010-0757-3openalex-snapshot
Solving the Rectangular assignment problem and applications
inferred← citeshttps://doi.org/10.1007/s11590-021-01791-4openalex-snapshot
The assignment problem revisited
inferred← citeshttps://doi.org/10.1016/0743-7315(91)90092-nopenalex-snapshot
On the massively parallel solution of the assignment problem
inferred← citeshttps://doi.org/10.1016/j.jpdc.2024.104838openalex-snapshot
HyLAC: Hybrid linear assignment solver in CUDA
inferred← citeshttps://doi.org/10.1016/j.rico.2024.100383openalex-snapshot
New auction algorithms for the assignment problem and extensions
inferred← citeshttps://doi.org/10.1016/s0166-218x(99)00172-9openalex-snapshot
Algorithms and codes for dense assignment problems: the state of the art
inferred← citeshttps://doi.org/10.1016/s0927-0507(05)80122-7openalex-snapshot
Chapter 5 Parallel computing in network optimization
inferred← citeshttps://doi.org/10.1109/71.862206openalex-snapshot
A parallel pruning technique for highly asymmetric assignment problems
inferred← citeshttps://doi.org/10.1109/ccdc.2016.7531871openalex-snapshot
Zero element row augmenting path algorithm for linear assignment problems
inferred← citeshttps://doi.org/10.1109/taes.2016.140952openalex-snapshot
On implementing 2D rectangular assignment algorithms
inferred← citeshttps://doi.org/10.1109/tits.2025.3596607openalex-snapshot
A Multi-Task Scheduling Decision-Making Approach for SAEV Fleets: Integrating Stochastic Demand and Long-Term Benefit
inferred← citeshttps://doi.org/10.48550/arxiv.1810.03562openalex-snapshot
The equivalence between two classic algorithms for the assignment problem
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