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This is an unbalanced assignment problem. One way to solve it is to invent a fourth dummy task, perhaps called "sitting still doing nothing", with a cost of 0 for the taxi assigned to it. This reduces the problem to a balanced assignment problem, which can then be solved in the usual way and still give the best solution to the problem.
The multidimensional assignment problem (MAP) is a fundamental combinatorial optimization problem which was introduced by William Pierskalla. [1] This problem can be seen as a generalization of the linear assignment problem. [2] In words, the problem can be described as follows: An instance of the problem has a number of agents (i.e ...
The Hungarian method is a combinatorial optimization algorithm that solves the assignment problem in polynomial time and which anticipated later primal–dual methods.It was developed and published in 1955 by Harold Kuhn, who gave it the name "Hungarian method" because the algorithm was largely based on the earlier works of two Hungarian mathematicians, Dénes Kőnig and Jenő Egerváry.
The formal definition of the bottleneck assignment problem is Given two sets, A and T, together with a weight function C : A × T → R. Find a bijection f : A → T such that the cost function: (, ()) is minimized.
For example, i = arr[i] = f() is equivalent to arr[i] = f(); i = arr[i]. In C++ they are also available for values of class types by declaring the appropriate return type for the assignment operator. In Python, assignment statements are not expressions and thus do not have a value. Instead, chained assignments are a series of statements with ...
Therefore, the problem of finding a minimum maximal matching is essentially equal to the problem of finding a minimum edge dominating set. [8] Both of these two optimization problems are known to be NP-hard ; the decision versions of these problems are classical examples of NP-complete problems. [ 9 ]
The ideas of the auction algorithm and ε-scaling [1] are also central in preflow-push algorithms for single commodity linear network flow problems. In fact the preflow-push algorithm for max-flow can be derived by applying the original 1979 auction algorithm to the max flow problem after reformulation as an assignment problem.
Fair random assignment (also called probabilistic one-sided matching) is a kind of a fair division problem. In an assignment problem (also called house-allocation problem or one-sided matching), there are m objects and they have to be allocated among n agents, such that each agent receives at most one object. Examples include the assignment of ...