INFORMS J. Appl. Anal.最新文献_第6页

Improving Sports Media's Crystal Ball for National Basketball Association Playoff Elimination 提高体育媒体对nba季后赛淘汰的预测

INFORMS J. Appl. Anal. Pub Date : 2021-03-01 DOI: 10.1287/inte.2020.1034

M. Husted, E. Olinick, A. Newman

{"title":"Improving Sports Media's Crystal Ball for National Basketball Association Playoff Elimination","authors":"M. Husted, E. Olinick, A. Newman","doi":"10.1287/inte.2020.1034","DOIUrl":"https://doi.org/10.1287/inte.2020.1034","url":null,"abstract":"The National Basketball Association (NBA) is divided into two conferences, each of which comprises 15 teams. At the end of the regular season, the top eight teams from each conference, based on winning percentage, compete in the playoffs. Mixed-integer-programming (MIP) models determine when a team has guaranteed its position in the playoffs (clinched) or, conversely, when it has been eliminated before the completion of the regular season. Our models incorporate a series of complex two-way tiebreaking criteria used by the NBA to determine how many more games are needed either to clinch or to avoid elimination. We compare the time at which a given team has clinched or been eliminated, in terms of the number of games played in the season to date, as posted in the NBA official standings, against results from our mixed-integer program. For the 2017–2018 season, when our models outperform those of the NBA, they do so by an average of 4.1 games. We also describe a scenario in which the NBA erroneously reported that the Boston Celtics had clinched a playoff spot and, conversely, show that the Golden State Warriors had clinched a playoff spot before the official announcement by the NBA.","PeriodicalId":430990,"journal":{"name":"INFORMS J. Appl. Anal.","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129841155","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}

引用次数: 0

Predicting and Explaining Pig Iron Production on Charcoal Blast Furnaces: A Machine Learning Approach 预测和解释木炭高炉生铁产量:一种机器学习方法

INFORMS J. Appl. Anal. Pub Date : 2021-02-16 DOI: 10.1287/INTE.2020.1058

Marcio Salles Melo Lima, E. Eryarsoy, D. Delen

{"title":"Predicting and Explaining Pig Iron Production on Charcoal Blast Furnaces: A Machine Learning Approach","authors":"Marcio Salles Melo Lima, E. Eryarsoy, D. Delen","doi":"10.1287/INTE.2020.1058","DOIUrl":"https://doi.org/10.1287/INTE.2020.1058","url":null,"abstract":"Pig iron, the source for a variety of iron-based products, is traded in commodity markets. Therefore, enhanced productivity has significant economic implications for the producers. Pig iron is mainly produced inside of tall, vertical, thermodynamic reactors called blast furnaces that run 24 hours a day. The blast furnaces are too complex to model explicitly and are generally regarded as black boxes. In this study, we design, develop, and deploy novel machine learning models on a rich data sample covering more than 20 production variables spanning nine years of actual operational period, collected at one of the largest pig iron production plants in Brazil. We show that, given the blast furnace parameters, machine learning models are capable of unveiling novel insights by illuminating the black box and successfully predicting production levels at different configurations. These prediction models can be used as decision aids to improve production efficiencies. We also perform a sensitivity analysis of the trained models to identify and rank the input variables according to their relative importance. We present our findings, which are largely in line with the existing literature, and confirm their validity, practicality, and usefulness through consultations with subject matter experts.","PeriodicalId":430990,"journal":{"name":"INFORMS J. Appl. Anal.","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121557584","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}

引用次数: 1

Saurabh Bansal, Karen E. Jenni, Jeffrey Keisler, Johannes Ulrich Siebert: Special Issue of INFORMS Journal on Applied Analytics - Decision Analysis Saurabh Bansal, Karen E. Jenni, Jeffrey Keisler, Johannes Ulrich Siebert: INFORMS应用分析杂志特刊-决策分析

INFORMS J. Appl. Anal. Pub Date : 2021-02-08 DOI: 10.1287/inte.2021.1072

K. Jenni, J. Keisler, J. Siebert

引用次数: 0

Network Mode Optimization for the DHL Supply Chain DHL供应链的网络模式优化

INFORMS J. Appl. Anal. Pub Date : 2021-02-05 DOI: 10.1287/INTE.2020.1046

Yibo Dang, Manjeet Singh, T. Allen

{"title":"Network Mode Optimization for the DHL Supply Chain","authors":"Yibo Dang, Manjeet Singh, T. Allen","doi":"10.1287/INTE.2020.1046","DOIUrl":"https://doi.org/10.1287/INTE.2020.1046","url":null,"abstract":"DHL Supply Chain North America moves more than 20 million packages each year. DHL transportation planners perform routing and cost-deduction tasks for many business projects. We refer to the associated planning problem as the Vehicle Routing Problem with Time Regulations and Common Carriers (VRPTRCC). Unlike ordinary vehicle routing problems, which use only a single type of transportation mode, our VRPTRCC applications include make–buy decisions because some of the package deliveries are ultimately subcontracted to organizations other than DHL. Time regulation means that the problem considers not only delivery-time windows, but also layover and driving-time restrictions. Our developed Network Mode Optimization Tool (NMOT) is an ant-colony optimization (ACO)-based program that aids DHL Supply Chain transportation analysts in identifying cost savings in the ground logistic network. By using the NMOT, DHL and its customers have saved millions of dollars annually. Also, the NMOT is helping DHL to win new customers against bidding competitors and reducing estimation times from multiple weeks to hours. The results show an actual increase in profits compared with the previous process by more than 15% through a combination of new projects enabled and reduced current operational costs. The NMOT is implemented and evaluated by using data from ongoing projects.","PeriodicalId":430990,"journal":{"name":"INFORMS J. Appl. Anal.","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128858619","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}

引用次数: 4

Practice Summary: Le Macaron Implements Ordering Optimization 实践总结:Le Macaron实现了订单优化

INFORMS J. Appl. Anal. Pub Date : 2020-12-28 DOI: 10.1287/inte.2020.1050

M. Gorman

引用次数: 3

Scheduling Multiple Sports Leagues with Travel Distance Fairness: An Application to Argentinean Youth Football 基于行程距离公平性的多个体育联赛调度:在阿根廷青少年足球中的应用

INFORMS J. Appl. Anal. Pub Date : 2020-12-18 DOI: 10.1287/inte.2020.1048

Guillermo Durán, M. Guajardo, Agustina F. López, J. Marenco, G. Zamorano

引用次数: 8

Editorial: Interfaces/INFORMS Journal on Applied Analytics Hall of Fame Contributors 社论:接口/INFORMS杂志应用分析名人堂贡献者

INFORMS J. Appl. Anal. Pub Date : 2020-11-04 DOI: 10.1287/inte.2020.1057

M. Gorman