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Amazon DynamoDB is a managed NoSQL database service provided by Amazon Web Services (AWS). It supports key-value and document data structures and is designed to handle a wide range of applications requiring scalability and performance.
Dynamo is a set of techniques that together can form a highly available key-value structured storage system [1] or a distributed data store. [1] It has properties of both databases and distributed hash tables (DHTs).
Multi-objective optimization or Pareto optimization (also known as multi-objective programming, vector optimization, multicriteria optimization, or multiattribute optimization) is an area of multiple-criteria decision making that is concerned with mathematical optimization problems involving more than one objective function to be optimized simultaneously.
There is a finite set of objects, denoted by M.There are n agents. Each agent i has a value-function V i, that assigns a value to each subset of objects.The goal is to partition M into n subsets, X 1,...,X n, and give each subset X i to agent i, such that the allocation is both Pareto-efficient and approximately fair.
In statistics, the generalized Pareto distribution (GPD) is a family of continuous probability distributions.It is often used to model the tails of another distribution. It is specified by three parameters: location , scale , and shape
A significant aspect of the Pareto frontier in economics is that, at a Pareto-efficient allocation, the marginal rate of substitution is the same for all consumers. [5] A formal statement can be derived by considering a system with m consumers and n goods, and a utility function of each consumer as = where = (,, …,) is the vector of goods, both for all i.
A Pareto chart is a type of chart that contains both bars and a line graph, where individual values are represented in descending order by bars, and the cumulative total is represented by the line. The chart is named for the Pareto principle , which, in turn, derives its name from Vilfredo Pareto , a noted Italian economist.
Given a set of resources and a set of agents, the goal is to divide the resources among the agents in a way that is both Pareto efficient (PE) and envy-free (EF). The goal was first defined by David Schmeidler and Menahem Yaari. [1] Later, the existence of such allocations has been proved under various conditions.