Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: A simple random walk with reflected origin is considered. The walk starts at the origin and it must return to the origin at time 2n.  show that the expected area below the path of this walk is n22n−1/Cn2n. If, hover, the walk is required to return to the origin for the first time at time 2n, then the expected area below the path of this Bernoulli excursion is (2n − 1)22n−1/Cn2n.  also show that if V1 < ⋯ < Vn is the order statistics based on a sample of size n from a uniform distribution over (0, 1), and that if U1 < ⋯ < Un is another independent set of order statistics from the same distribution, then E [∑i=1n |Vi − Ui|] = n22n−1/[(2n + 1)Cn2n]  use this result to find an average-case performance of the Earliest Due Date (EDD) heuristic for one machine scheduling problem with earliness and tardiness penalties.  also apply some of the results to Larson's Queue Inference Engine (1990).
['Arie Harel']
I am writing a research paper on a idea Random walk and the area below its path
[{"from": "human", "value": "I am writing a research paper on a idea Random walk and the area below its path"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: A simple random walk with reflected origin is considered. The walk starts at the origin and it must return to the origin at time 2n.  show that the expected area below the path of this walk is n22n\u22121/Cn2n. If, hover, the walk is required to return to the origin for the first time at time 2n, then the expected area below the path of this Bernoulli excursion is (2n \u2212 1)22n\u22121/Cn2n.  also show that if V1 < \u22ef < Vn is the order statistics based on a sample of size n from a uniform distribution over (0, 1), and that if U1 < \u22ef < Un is another independent set of order statistics from the same distribution, then E [\u2211i=1n |Vi \u2212 Ui|] = n22n\u22121/[(2n + 1)Cn2n]  use this result to find an average-case performance of the Earliest Due Date (EDD) heuristic for one machine scheduling problem with earliness and tardiness penalties.  also apply some of the results to Larson's Queue Inference Engine (1990)."}]