Online assignment mechanisms with applications in resource allocation
Abstract/Contents
- Abstract
- We study online assignment mechanisms in different contexts, namely online assignment mechanisms under fairness constraints and online bayesian selection problem under combinatorial constraints. In both cases, we design mechanisms that achieve a constant fraction of the optimum online policy in objective value. One common challenge we face in obtaining our results is generating a solution that satisfies all the structural constraints imposed by the problem. In doing so, we introduce several novel techniques for achieving and rounding our results
Description
| Type of resource | text |
|---|---|
| Form | electronic resource; remote; computer; online resource |
| Extent | 1 online resource |
| Place | California |
| Place | [Stanford, California] |
| Publisher | [Stanford University] |
| Copyright date | 2020; ©2020 |
| Publication date | 2020; 2020 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Author | Shameli, Seyed Ali |
|---|---|
| Degree supervisor | Saberi, Amin |
| Thesis advisor | Saberi, Amin |
| Thesis advisor | Ashlagi, Itai |
| Thesis advisor | Lo, Irene Man-Chi |
| Degree committee member | Ashlagi, Itai |
| Degree committee member | Lo, Irene Man-Chi |
| Associated with | Stanford University, Department of Management Science and Engineering |
Subjects
| Genre | Theses |
|---|---|
| Genre | Text |
Bibliographic information
| Statement of responsibility | Ali Shameli |
|---|---|
| Note | Submitted to the Department of Management Science and Engineering |
| Thesis | Thesis Ph.D. Stanford University 2020 |
| Location | electronic resource |
Access conditions
- Copyright
- © 2020 by Seyed Ali Shameli
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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