Decentralized resource allocation for synchronized tasks through Adaptive Large Neighborhood Search (ALNS)
Name
1191820965-MIT.pdf
Size
1.58 MB
Format
Adobe PDF
Checksum (MD5)
b6ddce2f99530febf0f070fd35e37240
Author(s)
Montgomery, Christian D.(Christian Donovan)
Advisor(s)
Hamsa Balakrishnan.
Date Issued
2020
Publisher
Massachusetts Institute of Technology
Abstract
This thesis explores a method for multiple suppliers to coordinate resource scheduling of task requests from multiple consumers using decentralized planning. A time window is associated with each task and some tasks require simultaneous servicing from multiple resources of specified classes to fulfil a request. The suppliers create schedules for their resources that maximize the value of all tasks fulfilled, while minimizing travel cost, and respecting all time window constraints. This thesis presents Infeasibility Cooling Adaptive Allocation for Resource United Scheduling (ICAARUS), a novel Adaptive Large Neighborhood Search (ALNS) algorithm that is capable of synchronizing tasks across a variable number of resources. A supplier's individual schedule and cost function is kept private from consumers. An e-commerce style of multi-round bidding is introduced to notify suppliers of resource request parameters and to allow consumers to synchronize resources from independent suppliers. A Mixed-Integer Linear Program (MILP) is used by the consumer to select the least costly bids that can be combined to fulfill a task's requirements.
Description
Thesis: S.M., Massachusetts Institute of Technology, Department of Aeronautics and Astronautics, May, 2020
Cataloged from the official PDF of thesis.
Includes bibliographical references (pages 91-93).
Subjects
Aeronautics and Astronautics.
MIT Department
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
Terms of Use
MIT theses may be protected by copyright. Please reuse MIT thesis content according to the MIT Libraries Permissions Policy, which is available through the URL provided.
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