{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/120578"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/120578","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"New algorithms exploiting randomness in lead times in inventory systems","abstract":"Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2025-05-01","abstract_html":"Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2025-05-01","abstract_has_math":false,"creators":["Taneja, Aditi"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"M.S.","degree_level":"Thesis","degree_discipline":"Industrial Engineering","degree_department":null,"school":null,"contributors":["Stolyar, Aleksandr","Wang, Qiong"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2023,"date_issued":"2023-05","date_published":"2023-05","updated_at":"2026-07-22T22:24:57Z","subjects":["Gbs","Pipeline","Cbs","Adaptive"],"languages":["en","eng"],"rights":["Copyright 2023 Aditi Taneja"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/2142/120578","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Stolyar, Aleksandr","Wang, Qiong"]},{"key":"dc:creator","label":"Author","values":["Taneja, Aditi"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2023-05","2023-05-04"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Industrial Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M.S."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Gbs","Pipeline","Cbs","Adaptive"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en","eng"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2023 Aditi Taneja"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://hdl.handle.net/2142/120578"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2025-05-01","The student, Aditi Taneja, accepted the attached license on 2023-04-30 at 11:46.","The student, Aditi Taneja, submitted this Thesis for approval on 2023-04-30 at 11:59.","This Thesis was approved for publication on 2023-05-04 at 17:02.","DSpace SAF Submission Ingestion Package generated from Vireo submission #19266 on 2023-09-01 at 17:22:14","In this work, we examine a traditional single-item inventory system where unfilled demands result in backlog. The time it takes to restock varies at random and is independent and identically distributed, leading to orders crossing paths.The research conducted by (1) demonstrates that the randomness of lead times in inventory systems can potentially result in infinite improvements compared to constant lead times. The aim of this project is to investigate the feasibility of achieving such improvements while considering practical system constraints and identifying policies that are both effective and practical. This study introduces two new policies, Adaptive and Pipeline, in addition to the discrete-time version of the Generalized Base Stock policy introduced in (1) and Constant Base Stock Policy ((2)). The performance of the four policies are evaluated through simulations, with a focus on the impact of lead time distributions. The results indicate that the proposed policies can lead to significant performance improvements under practical constraints, with larger improvements observed when lead time variability is higher. We find that the Pipeline policy is found to be the most effective and practical for implementation."]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["New algorithms exploiting randomness in lead times in inventory systems"]}]}],"canonical_facts":{"dc:contributor":["Stolyar, Aleksandr","Wang, Qiong"],"dc:creator":["Taneja, Aditi"],"dc:date":["2023-05","2023-05-04"],"dc:description":["Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2025-05-01","The student, Aditi Taneja, accepted the attached license on 2023-04-30 at 11:46.","The student, Aditi Taneja, submitted this Thesis for approval on 2023-04-30 at 11:59.","This Thesis was approved for publication on 2023-05-04 at 17:02.","DSpace SAF Submission Ingestion Package generated from Vireo submission #19266 on 2023-09-01 at 17:22:14","In this work, we examine a traditional single-item inventory system where unfilled demands result in backlog. The time it takes to restock varies at random and is independent and identically distributed, leading to orders crossing paths.The research conducted by (1) demonstrates that the randomness of lead times in inventory systems can potentially result in infinite improvements compared to constant lead times. The aim of this project is to investigate the feasibility of achieving such improvements while considering practical system constraints and identifying policies that are both effective and practical. This study introduces two new policies, Adaptive and Pipeline, in addition to the discrete-time version of the Generalized Base Stock policy introduced in (1) and Constant Base Stock Policy ((2)). The performance of the four policies are evaluated through simulations, with a focus on the impact of lead time distributions. The results indicate that the proposed policies can lead to significant performance improvements under practical constraints, with larger improvements observed when lead time variability is higher. We find that the Pipeline policy is found to be the most effective and practical for implementation."],"dc:format":["application/pdf"],"dc:identifier":["https://hdl.handle.net/2142/120578"],"dc:language":["en","eng"],"dc:rights":["Copyright 2023 Aditi Taneja"],"dc:subject":["Gbs","Pipeline","Cbs","Adaptive"],"dc:title":["New algorithms exploiting randomness in lead times in inventory systems"],"dc:type":["text"],"thesis:degree_discipline":["Industrial Engineering"],"thesis:degree_level":["Thesis"],"thesis:degree_name":["M.S."],"thesis:institution_name":["University of Illinois at Urbana-Champaign"]},"updated_at":"2026-07-22T22:24:57Z"}