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Massachusetts Institute of Technology

Resource scheduling and optimization in dynamic and complex transportation settings

Abstract

dc:description.abstract

Resource optimization has always been a challenge both in traditional fields, such as logistics, and particularly so in most emerging systems in the sharing economy. These systems are by definition founded on the sharing of resources among users, which naturally creates many coordination needs as well as challenges to ensure enough resource supply to cover customer demand. This thesis addresses these challenges in the application of vehicle sharing systems, as well as in the context of multi-operation companies that provide a wide range of services to their users. More specifically, the first part of this thesis focuses on models and algorithms for the optimization of bike sharing systems. Shortage of bikes and docks is a common issue in bike sharing systems, and, to tackle this problem, operators use a fleet of vehicles to redistribute bikes across the network.

Degree

thesis:*
Name thesis:degree_name
Doctoral
Department dc:contributor.department
Massachusetts Institute of Technology. Operations Research Center
Grantor dc:publisher
Massachusetts Institute of Technology
Year dc:date.issued
2019

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Mellou, Konstantina.
Advisor dc:contributor.advisor
  • Patrick Jaillet.

Subjects

dc:subject × 1

Rights

dc:rights
Statement dc:rights
  • MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.
Language dc:language.iso
eng

Identifiers

dc:identifier.*
Handle dc:identifier.uri
https://hdl.handle.net/1721.1/122387
OAI identifier oai:identifier
oai:dspace.mit.edu:1721.1/122387

Chain of custody

source
Harvested from
MIT
Base URL
dspace.mit.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Mellou, Konstantina.. Resource scheduling and optimization in dynamic and complex transportation settings. Massachusetts Institute of Technology, 2019. https://hdl.handle.net/1721.1/122387