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Assignment problem

About: Assignment problem is a research topic. Over the lifetime, 7588 publications have been published within this topic receiving 172820 citations. The topic is also known as: marriage problem.


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01 Mar 2006
TL;DR: A suite of suboptimal, but computationally tractable (polynomial time) algorithms are given, based on a solution to the problem of finding the optimal translation and rotation given a fixed assignment.
Abstract: In this paper we study the problem of parameterized assignment. This problem arises when a team of mobile robots must decide what role to take on in a given planar formation, where the parameters are the rotation and translation of the formation. A suite of suboptimal, but computationally tractable (polynomial time) algorithms are given, based on a solution to the problem of finding the optimal translation and rotation given a fixed assignment. Numerical examples show the viability of the proposed, suboptimal solutions.

74 citations

Journal ArticleDOI
TL;DR: An algorithmic ``solution'' to the assignment problem of synchronous sequential machines is described, which can assign the input, state, and output symbols of a given machine so as to ``minimize'' the total logic.
Abstract: The purpose of this paper is to describe an algorithmic ``solution'' to the assignment problem of synchronous sequential machines. The figure of merit used provides a mathematical evaluation of the reduced dependencies that may exist in the set of logic equations. If desired, the algorithm can assign the input, state, and output symbols of a given machine so as to ``minimize'' the total logic, i.e., reduced dependencies of both the state and output logic on state and input variables are optimized. The method is nonenumerative in the sense that the first assignmnent found is optimal. A restricted version of the algorithm has been programmed for an IBM 7094 computer.

74 citations

Journal ArticleDOI
Mauricio Sadinle1
TL;DR: This paper argues that this independence assumption in the matching statuses of record pairs is unreasonable and proposes partial Bayes estimates that allow uncertain parts of the bipartite matching to be left unresolved and demonstrates the advantages of these methods merging two datafiles on casualties from the civil war of El Salvador.
Abstract: The bipartite record linkage task consists of merging two disparate datafiles containing information on two overlapping sets of entities. This is nontrivial in the absence of unique identifiers and it is important for a wide variety of applications given that it needs to be solved whenever we have to combine information from different sources. Most statistical techniques currently used for record linkage are derived from a seminal article by Fellegi and Sunter in 1969. These techniques usually assume independence in the matching statuses of record pairs to derive estimation procedures and optimal point estimators. We argue that this independence assumption is unreasonable and instead target a bipartite matching between the two datafiles as our parameter of interest. Bayesian implementations allow us to quantify uncertainty on the matching decisions and derive a variety of point estimators using different loss functions. We propose partial Bayes estimates that allow uncertain parts of the bipartite...

74 citations

Journal ArticleDOI
TL;DR: An efficient (polynomial time) solution for a single machine scheduling and due-window assignment problem to minimize the total cost consisting of earliness, tardiness, andDue-window starting time and size is introduced.

74 citations

Journal ArticleDOI
TL;DR: In this article, a dynamic approach is proposed to face on-line operation conditions for assigning planes to flights and fleet maintenance operations scheduling in a medium-charter airline, where the proposed solution mixes a Dynamic Programming approach (to cope with the fleet assignment problem) and a heuristic technique (to solve the embedded maintenance schedule problem).

74 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202331
202298
2021303
2020339
2019342
2018326