Auction Algorithm: Difference between revisions
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== The Assignment Problem == | == The Assignment Problem == | ||
It is necessary to introduce the assignment problem because it applies a context in which we may apply our algorithm to find such an optimal equilibrium. Suppose we have both <math> N </math> buyers as well as <math> N </math> goods. We introduce <math> u_{ij} </math> to quantify the notion of some sort of utility, benefit, or happiness the buyer receives from their corresponding good. | It is necessary to introduce the assignment problem because it applies a context in which we may apply our algorithm to find such an optimal equilibrium. Suppose we have both <math> N </math> buyers as well as <math> N </math> goods. We introduce <math> u_{ij} </math> to quantify the notion of some sort of utility, benefit, or happiness the buyer receives from their corresponding good. The assignment problem therefore seeks a way to maximize <math> \sum_i </math> | ||
Revision as of 20:21, 14 May 2020
The auction algorithm[1] is an algorithm in optimal transport in which a set of buyers exchange goods for varied prices until an eventual equilibrium is reached. It is an iterative approach. The algorithm pertains to the discrete formulation of optimal transport, as well as provides a connection to the dual problem. The algorithm is useful in the field of economics because of its ability to find an equilibrium. The algorithm was invented by Bertsekas, but it was eventually updated.
The Assignment Problem
It is necessary to introduce the assignment problem because it applies a context in which we may apply our algorithm to find such an optimal equilibrium. Suppose we have both buyers as well as goods. We introduce to quantify the notion of some sort of utility, benefit, or happiness the buyer receives from their corresponding good. The assignment problem therefore seeks a way to maximize
References
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