View in EDS HTML Full Text PDF Full Text

Algorithmic Precision and Human Decision: A Study of Interactive Optimization for School Schedules.

Saved in:
Bibliographic Details
Authors: Delarue, Arthur1 (AUTHOR) arthur.delarue@isye.gatech.edu, Lian, Zhen2 (AUTHOR) zhen.lian@yale.edu, Martin, Sebastien3 (AUTHOR) sebastien.martin@kellogg.northwestern.edu
Source: Management Science (INFORMS). Jan2026, Vol. 72 Issue 1, p148-166. 19p.
Subject Terms: *Mathematical optimization, *Transportation costs, *Decision making, *Government policy, School schedules, School districts, Statistical accuracy
Geographic Terms: United States
Abstract: In collaboration with the San Francisco Unified School District (SFUSD), this paper introduces an interactive optimization framework to tackle complex school scheduling challenges. The choice of school start and end times is an optimization challenge, as schedules influence the district's transportation system, and limiting the associated costs is a computationally difficult combinatorial problem. However, it is also a policy challenge, as transportation costs are far from the only consequence of school schedule changes. Policymakers need time and knowledge to balance these considerations and reach a consensus carefully; past implementations have failed because of policy issues, despite state-of-the-art optimization approaches. We first motivate our approach with a microfoundation model of the interplay between policymakers and researchers, arguing that limiting their dependency is key. Building on these insights, we propose a framework that includes (1) a fast algorithm capable of solving the school schedule problem that compares favorably to the literature and (2) an interactive optimization approach that leverages this speed to allow policymakers to explore a variety of solutions in a transparent and efficient way, facilitating the policy decision-making process. The framework led to the first optimization-driven school start time changes in the United States, updating the schedule of all 133 schools in SFUSD in 2021, with annual transportation savings exceeding $5 million. A comprehensive survey of approximately 27,000 parents and staff in 2022 provides evidence of the approach's effectiveness. [ABSTRACT FROM AUTHOR]
Database: Entrepreneurial Studies Source
Full text is not displayed to guests.
FullText Links:
  – Type: pdflink
Text:
  Availability: 1
Header DbId: ent
DbLabel: Entrepreneurial Studies Source
An: 190748682
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Delarue%2C+Arthur%22">Delarue, Arthur</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> arthur.delarue@isye.gatech.edu</i><br /><searchLink fieldCode="AR" term="%22Lian%2C+Zhen%22">Lian, Zhen</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> zhen.lian@yale.edu</i><br /><searchLink fieldCode="AR" term="%22Martin%2C+Sebastien%22">Martin, Sebastien</searchLink><relatesTo>3</relatesTo> (AUTHOR)<i> sebastien.martin@kellogg.northwestern.edu</i>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22Management+Science+%28INFORMS%29%22">Management Science (INFORMS)</searchLink>. Jan2026, Vol. 72 Issue 1, p148-166. 19p.
– Name: Subject
  Label: Subject Terms
  Group: Su
  Data: *<searchLink fieldCode="DE" term="%22Mathematical+optimization%22">Mathematical optimization</searchLink><br />*<searchLink fieldCode="DE" term="%22Transportation+costs%22">Transportation costs</searchLink><br />*<searchLink fieldCode="DE" term="%22Decision+making%22">Decision making</searchLink><br />*<searchLink fieldCode="DE" term="%22Government+policy%22">Government policy</searchLink><br /><searchLink fieldCode="DE" term="%22School+schedules%22">School schedules</searchLink><br /><searchLink fieldCode="DE" term="%22School+districts%22">School districts</searchLink><br /><searchLink fieldCode="DE" term="%22Statistical+accuracy%22">Statistical accuracy</searchLink>
– Name: SubjectGeographic
  Label: Geographic Terms
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22United+States%22">United States</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: In collaboration with the San Francisco Unified School District (SFUSD), this paper introduces an interactive optimization framework to tackle complex school scheduling challenges. The choice of school start and end times is an optimization challenge, as schedules influence the district's transportation system, and limiting the associated costs is a computationally difficult combinatorial problem. However, it is also a policy challenge, as transportation costs are far from the only consequence of school schedule changes. Policymakers need time and knowledge to balance these considerations and reach a consensus carefully; past implementations have failed because of policy issues, despite state-of-the-art optimization approaches. We first motivate our approach with a microfoundation model of the interplay between policymakers and researchers, arguing that limiting their dependency is key. Building on these insights, we propose a framework that includes (1) a fast algorithm capable of solving the school schedule problem that compares favorably to the literature and (2) an interactive optimization approach that leverages this speed to allow policymakers to explore a variety of solutions in a transparent and efficient way, facilitating the policy decision-making process. The framework led to the first optimization-driven school start time changes in the United States, updating the schedule of all 133 schools in SFUSD in 2021, with annual transportation savings exceeding $5 million. A comprehensive survey of approximately 27,000 parents and staff in 2022 provides evidence of the approach's effectiveness. [ABSTRACT FROM AUTHOR]
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=ent&AN=190748682
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1287/mnsc.2024.05834
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 19
        StartPage: 148
    Subjects:
      – SubjectFull: Mathematical optimization
        Type: general
      – SubjectFull: Transportation costs
        Type: general
      – SubjectFull: Decision making
        Type: general
      – SubjectFull: Government policy
        Type: general
      – SubjectFull: School schedules
        Type: general
      – SubjectFull: School districts
        Type: general
      – SubjectFull: Statistical accuracy
        Type: general
      – SubjectFull: United States
        Type: general
    Titles:
      – TitleFull: Algorithmic Precision and Human Decision: A Study of Interactive Optimization for School Schedules.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Delarue, Arthur
      – PersonEntity:
          Name:
            NameFull: Lian, Zhen
      – PersonEntity:
          Name:
            NameFull: Martin, Sebastien
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 01
              Text: Jan2026
              Type: published
              Y: 2026
          Identifiers:
            – Type: issn-print
              Value: 00251909
          Numbering:
            – Type: volume
              Value: 72
            – Type: issue
              Value: 1
          Titles:
            – TitleFull: Management Science (INFORMS)
              Type: main
ResultId 1