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Random priority (RP), [1] also called Random serial dictatorship (RSD), [2] is a procedure for fair random assignment - dividing indivisible items fairly among people. Suppose partners have to divide (or fewer) different items among them. Since the items are indivisible, some partners will necessarily get the less-preferred items (or no items ...
A powerful balls-into-bins paradigm is the "power of two random choices [2]" where each ball chooses two (or more) random bins and is placed in the lesser-loaded bin. This paradigm has found wide practical applications in shared-memory emulations, efficient hashing schemes, randomized load balancing of tasks on servers, and routing of packets ...
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.
In the fair random assignment problem, there are n objects and n people with different preferences over the objects. It is required to give an object to each person. To attain fairness, the allocation is randomized: for each (person, object) pair, a probability is calculated, such that the sum of probabilities for each person and for each ...
Random assignment or random placement is an experimental technique for assigning human participants or animal subjects to different groups in an experiment (e.g., a treatment group versus a control group) using randomization, such as by a chance procedure (e.g., flipping a coin) or a random number generator. [1]
First-fit (FF) is an online algorithm for bin packing.Its input is a list of items of different sizes. Its output is a packing - a partition of the items into bins of fixed capacity, such that the sum of sizes of items in each bin is at most the capacity.
Randomization is a statistical process in which a random mechanism is employed to select a sample from a population or assign subjects to different groups. [1] [2] [3] The process is crucial in ensuring the random allocation of experimental units or treatment protocols, thereby minimizing selection bias and enhancing the statistical validity. [4]
For example, consider a quadrant (circular sector) inscribed in a unit square. Given that the ratio of their areas is π / 4 , the value of π can be approximated using the Monte Carlo method: [1] Draw a square, then inscribe a quadrant within it. Uniformly scatter a given number of points over the square.