Randomized parallel algorithms for the multidimensional assignment problem

The multidimensional assignment problem (MAP) is a combinatorial optimization problem arising in diverse applications such as computer vision and motion tracking. In the MAP, the objective is to match tuples of objects with minimum total cost. Randomized parallel algorithms are proposed to solve MAP...

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Bibliographic Details
Published in:Applied numerical mathematics Vol. 49; no. 1; pp. 117 - 133
Main Authors: Oliveira, Carlos A.S., Pardalos, Panos M.
Format: Journal Article Conference Proceeding
Language:English
Published: Amsterdam Elsevier B.V 01.04.2004
Elsevier
Subjects:
Algorithmics. Computability. Computer arithmetics
Applied sciences
Calculus of variations and optimal control
Computer science; control theory; systems
Exact sciences and technology
Heuristics
Mathematical analysis
Mathematical programming
Mathematics
Multidimensional assignment problem
Operational research and scientific management
Operational research. Management science
Parallel algorithms
Randomized algorithms
Sciences and techniques of general use
Theoretical computing
Randomized algorithms
Multidimensional assignment problem
Parallel algorithms
Heuristics
Computer vision
Parallel algorithm
Numerical analysis
Applied mathematics
Optimization method
Randomized algorithm
Combinatorial optimization
ISSN:0168-9274, 1873-5460
Online Access:Get full text
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Summary:The multidimensional assignment problem (MAP) is a combinatorial optimization problem arising in diverse applications such as computer vision and motion tracking. In the MAP, the objective is to match tuples of objects with minimum total cost. Randomized parallel algorithms are proposed to solve MAPs appearing in multi-sensor multi-target applications. A parallel construction heuristic is described, together with some variations, as well as a parallel local search heuristic. Experimental results using the proposed algorithms are discussed.
ISSN:0168-9274
1873-5460
DOI:10.1016/j.apnum.2003.11.014