Optimizing the application order under precedent-based decision-making Article Swipe
Rossella Argenziano
,
Itzhak Gilboa
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1073/pnas.2509985122
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1073/pnas.2509985122
We study the decision problem of a Proposer who has a set of applications to submit for approval to an Authority and can choose an order of submission. The Proposer’s utility depends on the Authority’s rulings. The Authority has to be consistent with its past decisions, which we model using the nearest-neighbor criterion. If the Proposer’s utility increases with the set of approved applications, then any greedy strategy is optimal for her: She should submit any application that, given the current history, would be approved. However, if her utility increases with some approvals but decreases with others, the Proposer’s problem becomes significantly more complex. In the single-dimensional case, an optimal strategy can be computed in polynomial time. In the general case, however, finding an optimal strategy is NP-hard. Thus, even in the absence of uncertainty or strategic behavior on the part of the Authority, evaluating the impact of current submissions on future outcomes can be computationally intractable.
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Metadata
- Type
- article
- Language
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- Landing Page
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https://openalex.org/W4412493907Canonical identifier for this work in OpenAlex
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https://doi.org/10.1073/pnas.2509985122Digital Object Identifier
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Optimizing the application order under precedent-based decision-makingWork title
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articleOpenAlex work type
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enPrimary language
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2025Year of publication
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2025-07-18Full publication date if available
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Rossella Argenziano, Itzhak GilboaList of authors in order
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https://doi.org/10.1073/pnas.2509985122Publisher landing page
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YesWhether a free full text is available
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hybridOpen access status per OpenAlex
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https://doi.org/10.1073/pnas.2509985122Direct OA link when available
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Order (exchange), Set (abstract data type), Computer science, Operations research, Mathematical optimization, Mathematical economics, Greedy algorithm, Economics, Mathematics, Algorithm, Finance, Programming languageTop concepts (fields/topics) attached by OpenAlex
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0Total citation count in OpenAlex
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.has | 9, 38 |
| abstract_inverted_index.her | 87 |
| abstract_inverted_index.its | 43 |
| abstract_inverted_index.set | 11, 60 |
| abstract_inverted_index.the | 2, 33, 50, 54, 59, 79, 97, 105, 118, 131, 139, 142, 145 |
| abstract_inverted_index.who | 8 |
| abstract_inverted_index.even | 129 |
| abstract_inverted_index.her: | 71 |
| abstract_inverted_index.more | 102 |
| abstract_inverted_index.part | 140 |
| abstract_inverted_index.past | 44 |
| abstract_inverted_index.some | 91 |
| abstract_inverted_index.then | 64 |
| abstract_inverted_index.with | 42, 58, 90, 95 |
| abstract_inverted_index.Thus, | 128 |
| abstract_inverted_index.case, | 107, 120 |
| abstract_inverted_index.given | 78 |
| abstract_inverted_index.model | 48 |
| abstract_inverted_index.order | 25 |
| abstract_inverted_index.study | 1 |
| abstract_inverted_index.that, | 77 |
| abstract_inverted_index.time. | 116 |
| abstract_inverted_index.using | 49 |
| abstract_inverted_index.which | 46 |
| abstract_inverted_index.would | 82 |
| abstract_inverted_index.choose | 23 |
| abstract_inverted_index.future | 151 |
| abstract_inverted_index.greedy | 66 |
| abstract_inverted_index.impact | 146 |
| abstract_inverted_index.should | 73 |
| abstract_inverted_index.submit | 15, 74 |
| abstract_inverted_index.absence | 132 |
| abstract_inverted_index.becomes | 100 |
| abstract_inverted_index.current | 80, 148 |
| abstract_inverted_index.depends | 31 |
| abstract_inverted_index.finding | 122 |
| abstract_inverted_index.general | 119 |
| abstract_inverted_index.optimal | 69, 109, 124 |
| abstract_inverted_index.others, | 96 |
| abstract_inverted_index.problem | 4, 99 |
| abstract_inverted_index.utility | 30, 56, 88 |
| abstract_inverted_index.However, | 85 |
| abstract_inverted_index.NP-hard. | 127 |
| abstract_inverted_index.Proposer | 7 |
| abstract_inverted_index.approval | 17 |
| abstract_inverted_index.approved | 62 |
| abstract_inverted_index.behavior | 137 |
| abstract_inverted_index.complex. | 103 |
| abstract_inverted_index.computed | 113 |
| abstract_inverted_index.decision | 3 |
| abstract_inverted_index.history, | 81 |
| abstract_inverted_index.however, | 121 |
| abstract_inverted_index.outcomes | 152 |
| abstract_inverted_index.rulings. | 35 |
| abstract_inverted_index.strategy | 67, 110, 125 |
| abstract_inverted_index.Authority | 20, 37 |
| abstract_inverted_index.approvals | 92 |
| abstract_inverted_index.approved. | 84 |
| abstract_inverted_index.decreases | 94 |
| abstract_inverted_index.increases | 57, 89 |
| abstract_inverted_index.strategic | 136 |
| abstract_inverted_index.Authority, | 143 |
| abstract_inverted_index.consistent | 41 |
| abstract_inverted_index.criterion. | 52 |
| abstract_inverted_index.decisions, | 45 |
| abstract_inverted_index.evaluating | 144 |
| abstract_inverted_index.polynomial | 115 |
| abstract_inverted_index.application | 76 |
| abstract_inverted_index.submission. | 27 |
| abstract_inverted_index.submissions | 149 |
| abstract_inverted_index.uncertainty | 134 |
| abstract_inverted_index.Proposer’s | 29, 55, 98 |
| abstract_inverted_index.applications | 13 |
| abstract_inverted_index.intractable. | 156 |
| abstract_inverted_index.Authority’s | 34 |
| abstract_inverted_index.applications, | 63 |
| abstract_inverted_index.significantly | 101 |
| abstract_inverted_index.computationally | 155 |
| abstract_inverted_index.nearest-neighbor | 51 |
| abstract_inverted_index.single-dimensional | 106 |
| cited_by_percentile_year | |
| countries_distinct_count | 4 |
| institutions_distinct_count | 2 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/16 |
| sustainable_development_goals[0].score | 0.7699999809265137 |
| sustainable_development_goals[0].display_name | Peace, Justice and strong institutions |
| citation_normalized_percentile.value | 0.34399154 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |