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US Patent 10261837 Two-part job scheduling with capacity constraints and preferences

Patent 10261837 was granted and assigned to Sas (company) on April, 2019 by the United States Patent and Trademark Office.

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Contents

Is a
Patent
Patent

Patent attributes

Patent Applicant
Sas (company)
Sas (company)
Current Assignee
Sas (company)
Sas (company)
Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
Patent Number
10261837
Date of Patent
April 16, 2019
Patent Application Number
16023949
Date Filed
June 29, 2018
Patent Citations Received
‌
US Patent 11687864 Method and system for summarizing user activities of tasks into a single activity score using machine learning to predict probabilities of completeness of the tasks
0
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US Patent 10977097 Notifying entities of relevant events
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US Patent 11025693 Event detection from signal data removing private information
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US Patent 11055639 Optimizing manufacturing processes using one or more machine learning models
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US Patent 10506008 Detecting an event from streaming data
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US Patent 10581945 Detecting an event from signal data
Patent Primary Examiner
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Wissam Rashid
Patent abstract

Exemplary embodiments relate to the problem of allocating a finite number of units of a resource among requestors willing to offer different amounts of value for the resource. When different classes of requestors are permitted to cancel the request or fail to show up to collect the unit of the resource with different probabilities (collectively referred to as “wash”), the problem becomes difficult to solve efficiently. According to the procedures described herein, the capacity is artificially inflated to offset the impact of wash, and then protection levels are computed using the inflated capacity as if there was no wash. The capacity is then artificially inflated again based on the new protection levels, and the process is repeated until, e.g., the results converge. Using this procedure, overallocation limits and protection levels can be computed in real-time, and accordingly the resource can be allocated efficiently as new requests are received.

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