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It is also known as the marriage problem, the sultan's dowry problem, the fussy suitor problem, the googol game, and the best choice problem. Its solution is also known as the 37% rule. [3] The basic form of the problem is the following: imagine an administrator who wants to hire the best secretary out of rankable applicants for a position. The ...
Gale–Shapley algorithm. In mathematics, economics, and computer science, the Gale–Shapley algorithm (also known as the deferred acceptance algorithm, [1] propose-and-reject algorithm, [2] or Boston Pool algorithm[1]) is an algorithm for finding a solution to the stable matching problem. It is named for David Gale and Lloyd Shapley, who ...
Stable marriage problem. In mathematics, economics, and computer science, the stable marriage problem (also stable matching problem) is the problem of finding a stable matching between two equally sized sets of elements given an ordering of preferences for each element. A matching is a bijection from the elements of one set to the elements of ...
In mathematics, marriage problem may refer to: Assignment problem, consisting of finding a maximum weight matching in a weighted bipartite graph. Secretary problem, also called the sultan's dowry or best choice problem, in optimal stopping theory. Stable marriage problem, the problem of finding a stable matching between two equally sized sets ...
Key Estate Planning Considerations for Second Marriages. Remarriage can bring up a number of important questions for estate planning. Both spouses should be aware of what the central issues are ...
Optimal stopping. In mathematics, the theory of optimal stopping[1][2] or early stopping[3] is concerned with the problem of choosing a time to take a particular action, in order to maximise an expected reward or minimise an expected cost. Optimal stopping problems can be found in areas of statistics, economics, and mathematical finance ...
The missionaries and cannibals problem, and the closely related jealous husbands problem, are classic river-crossing logic puzzles. [1] The missionaries and cannibals problem is a well-known toy problem in artificial intelligence, where it was used by Saul Amarel as an example of problem representation. [2][3]
Unlike marketplaces, where problems are solved by establishing pricing mechanisms and then allowing the participants to find optimal solutions among themselves, allocation problems happen when pricing is impractical or undesirable, such as assigning donated organs to surgery patients, students to schools, or refugees to host cities.
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