{"title":"Hybrid Scheduling with Mixed-Integer Programming at Columbia Business School","authors":"C. Moallemi, Utkarsh Patange","doi":"10.1287/inte.2022.0070","DOIUrl":"https://doi.org/10.1287/inte.2022.0070","url":null,"abstract":"For classroom scheduling during the COVID-19 pandemic, we develop several variations of mixed integer programs where we seek to balance multiple objectives and constraints, including maximizing in-person attendance while maintaining social distancing constraints and balancing in-person attendance across students and over time.","PeriodicalId":510763,"journal":{"name":"INFORMS Journal on Applied Analytics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139250735","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Stop Auditing and Start to CARE: Paradigm Shift in Assessing and Improving Supplier Sustainability","authors":"Tarkan Tan, M. H. Akyüz, B. Urlu, Santiago Ruiz","doi":"10.1287/inte.2022.0015","DOIUrl":"https://doi.org/10.1287/inte.2022.0015","url":null,"abstract":"Traditional auditing has been commonly practiced by multinational companies to monitor their suppliers for sustainability violations. Based on a collaborative supplier sustainability performance improvement program at Koninklijke (Royal) Philips N.V., we introduce a framework that offers a paradigm shift to an improvement-based proactive approach that makes use of suppliers’ self-assessments. We refer to this framework as CARE, consisting of the following phases: collecting supplier sustainability data, assessing suppliers’ sustainability levels, reacting to future violations proactively, and enhancing sustainability performance. The framework integrates analytics techniques to understand the link between the general characteristics of the carefully assessed suppliers—such as location, size, and sector—and their sustainability profile, enabling large-scale supplier assessment and improvement. This information is then used to leverage machine learning techniques to predict current and future sustainability levels of suppliers and to determine best actions for sustainability improvement using mathematical programming. The utilization of analytics constitutes a pivotal element in this endeavor and notably makes CARE highly scalable because it harnesses limited supplier data—namely, only general supplier information—while there is a need to support decision making concerning thousands of suppliers. Philips makes use of this framework and reports that the overall 2021 year-on-year improvement in sustainability performance was 24% for suppliers that entered the program in 2020, indicating the efficacy of the suggested approach. History: This paper was refereed. Funding: The authors gratefully acknowledge the support of TKI Dinalog–Dutch Institute for Advance Logistics on the project entitled “Supplier Sustainability Improvement” [Grant 2017-2-132TKI].","PeriodicalId":510763,"journal":{"name":"INFORMS Journal on Applied Analytics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139271905","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Practice Summary: General Electric Company Optimizes Wind Turbine Towers Sourcing and Logistics Operations","authors":"Srinivas Bollapragada","doi":"10.1287/inte.2022.0058","DOIUrl":"https://doi.org/10.1287/inte.2022.0058","url":null,"abstract":"General Electric’s Renewable Energy business used to manually make annual sourcing and logistics plans to procure wind turbine towers from suppliers across the world and deliver them to customer sites. This process was time-consuming, cumbersome, suboptimal, and increased the cost of fulfilling customer demands. We developed an algorithm and a software tool to generate near-optimal towers’ sourcing and logistics plans, which minimized the total direct material and logistics costs incurred.","PeriodicalId":510763,"journal":{"name":"INFORMS Journal on Applied Analytics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139272754","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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