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The original, and best-known, example of an apportionment problem involves distributing seats in a legislature between different federal states or political parties. [1] However, apportionment methods can be applied to other situations as well, including bankruptcy problems , [ 2 ] inheritance law (e.g. dividing animals ), [ 3 ] [ 4 ] manpower ...
An example of the apportionment paradox known as "the Alabama paradox" was discovered in the context of United States congressional apportionment in 1880, [1]: 228–231 when census calculations found that if the total number of seats in the House of Representatives were hypothetically increased, this would decrease Alabama's seats from 8 to 7.
The problem has two parts: what aspect ratios are possible, and how many different solutions are there for a given n. [7] Frieling and Rinne had previously published a result in 1994 that states that the aspect ratio of rectangles in these dissections must be an algebraic number and that each of its conjugates must have a positive real part. [3]
Two of the problems are trivial (the number of equivalence classes is 0 or 1), five problems have an answer in terms of a multiplicative formula of n and x, and the remaining five problems have an answer in terms of combinatorial functions (Stirling numbers and the partition function for a given number of parts).
In the balanced assignment problem, both parts of the bipartite graph have the same number of vertices, denoted by n. One of the first polynomial-time algorithms for balanced assignment was the Hungarian algorithm. It is a global algorithm – it is based on improving a matching along augmenting paths (alternating paths between unmatched vertices).
The problem is known to undergo a "phase transition"; being likely for some sets and unlikely for others. If m is the number of bits needed to express any number in the set and n is the size of the set then / < tends to have many solutions and / > tends to have few or no solutions. As n and m get larger, the probability of a perfect partition ...
Such a partition is called a partition with distinct parts. If we count the partitions of 8 with distinct parts, we also obtain 6: 8; 7 + 1; 6 + 2; 5 + 3; 5 + 2 + 1; 4 + 3 + 1; This is a general property. For each positive number, the number of partitions with odd parts equals the number of partitions with distinct parts, denoted by q(n).
The PARSE keyword instruction makes it possible to quickly and flexibly parse a string and assign parts of it to variables in a single step. [2] Subsequent instruction is used to specify the source of the string, for example ARG for arguments that are listed when the program or function is called, VAR for variables, PULL for data queues or ...