Najib Errami, Eduardo Queiroga, Ruslan Sadykov, Eduardo Uchoa
INFORMS Journal on Computing, Ahead of Print.
INFORMS 计算期刊》，印刷版。
{"title":"VRPSolverEasy: A Python Library for the Exact Solution of a Rich Vehicle Routing Problem","authors":"Najib Errami, Eduardo Queiroga, Ruslan Sadykov, Eduardo Uchoa","doi":"10.1287/ijoc.2023.0103","DOIUrl":"https://doi.org/10.1287/ijoc.2023.0103","url":null,"abstract":"INFORMS Journal on Computing, Ahead of Print. <br/>","PeriodicalId":13620,"journal":{"name":"Informs Journal on Computing","volume":"11 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2023-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139062978","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Minimizing the Weighted Number of Tardy Jobs via (max,+)-Convolutions","authors":"Danny Hermelin, Hendrik Molter, Dvir Shabtay","doi":"10.1287/ijoc.2022.0307","DOIUrl":"https://doi.org/10.1287/ijoc.2022.0307","url":null,"abstract":"INFORMS Journal on Computing, Ahead of Print. <br/>","PeriodicalId":13620,"journal":{"name":"Informs Journal on Computing","volume":"250 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2023-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139027782","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We apply supervised learning to a general problem in queueing theory: using a neural net, we develop a fast and accurate predictor of the stationary system-length distribution of a GI/GI/1 queue—a fundamental queueing model for which no analytical solutions are available. To this end, we must overcome three main challenges: (i) generating a large library of training instances that cover a wide range of arbitrary interarrival and service time distributions, (ii) labeling the training instances, and (iii) providing continuous arrival and service distributions as inputs to the neural net. To overcome (i), we develop an algorithm to sample phase-type interarrival and service time distributions with complex transition structures. We demonstrate that our distribution-generating algorithm indeed covers a wide range of possible positive-valued distributions. For (ii), we label our training instances via quasi-birth-and-death(QBD) that was used to approximate PH/PH/1 (with phase-type arrival and service process) as labels for the training data. For (iii), we find that using only the first five moments of both the interarrival and service times distribution as inputs is sufficient to train the neural net. Our empirical results show that our neural model can estimate the stationary behavior of the GI/GI/1—far exceeding other available methods in terms of both accuracy and runtimes. History: Ram Ramesh, Area Editor for Data Science and Machine Learning. Funding: O. Baron received financial support from the Natural Sciences and Engineering Research Council of Canada (NERC) [Grant 458051]. D. Krass received financial support from the NERC [Grant 458395]. Supplemental Material: The software that supports the findings of this study is available within the paper and its Supplemental Information ( https://pubsonline.informs.org/doi/suppl/10.1287/ijoc.2022.0263 ) as well as from the IJOC GitHub software repository ( https://github.com/INFORMSJoC/2022.0263 ). The complete IJOC Software and Data Repository is available at https://informsjoc.github.io/ .
{"title":"Supervised ML for Solving the GI/GI/1 Queue","authors":"Opher Baron, Dmitry Krass, Arik Senderovich, Eliran Sherzer","doi":"10.1287/ijoc.2022.0263","DOIUrl":"https://doi.org/10.1287/ijoc.2022.0263","url":null,"abstract":"We apply supervised learning to a general problem in queueing theory: using a neural net, we develop a fast and accurate predictor of the stationary system-length distribution of a GI/GI/1 queue—a fundamental queueing model for which no analytical solutions are available. To this end, we must overcome three main challenges: (i) generating a large library of training instances that cover a wide range of arbitrary interarrival and service time distributions, (ii) labeling the training instances, and (iii) providing continuous arrival and service distributions as inputs to the neural net. To overcome (i), we develop an algorithm to sample phase-type interarrival and service time distributions with complex transition structures. We demonstrate that our distribution-generating algorithm indeed covers a wide range of possible positive-valued distributions. For (ii), we label our training instances via quasi-birth-and-death(QBD) that was used to approximate PH/PH/1 (with phase-type arrival and service process) as labels for the training data. For (iii), we find that using only the first five moments of both the interarrival and service times distribution as inputs is sufficient to train the neural net. Our empirical results show that our neural model can estimate the stationary behavior of the GI/GI/1—far exceeding other available methods in terms of both accuracy and runtimes. History: Ram Ramesh, Area Editor for Data Science and Machine Learning. Funding: O. Baron received financial support from the Natural Sciences and Engineering Research Council of Canada (NERC) [Grant 458051]. D. Krass received financial support from the NERC [Grant 458395]. Supplemental Material: The software that supports the findings of this study is available within the paper and its Supplemental Information ( https://pubsonline.informs.org/doi/suppl/10.1287/ijoc.2022.0263 ) as well as from the IJOC GitHub software repository ( https://github.com/INFORMSJoC/2022.0263 ). The complete IJOC Software and Data Repository is available at https://informsjoc.github.io/ .","PeriodicalId":13620,"journal":{"name":"Informs Journal on Computing","volume":"52 4","pages":""},"PeriodicalIF":2.1,"publicationDate":"2023-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138951215","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ankit Bansal, Jean-Philippe Richard, Bjorn P. Berg, Yu-Li Huang
INFORMS Journal on Computing, Ahead of Print.
INFORMS 计算期刊》，印刷版。
{"title":"A Sequential Follower Refinement Algorithm for Robust Surgery Scheduling","authors":"Ankit Bansal, Jean-Philippe Richard, Bjorn P. Berg, Yu-Li Huang","doi":"10.1287/ijoc.2022.0191","DOIUrl":"https://doi.org/10.1287/ijoc.2022.0191","url":null,"abstract":"INFORMS Journal on Computing, Ahead of Print. <br/>","PeriodicalId":13620,"journal":{"name":"Informs Journal on Computing","volume":"81 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2023-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138824355","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Wei Xu, Jie Tang, Ka Fai Cedric Yiu, Jian Wen Peng
INFORMS Journal on Computing, Ahead of Print.
INFORMS 计算期刊》，印刷版。
{"title":"An Efficient Global Optimal Method for Cardinality Constrained Portfolio Optimization","authors":"Wei Xu, Jie Tang, Ka Fai Cedric Yiu, Jian Wen Peng","doi":"10.1287/ijoc.2022.0344","DOIUrl":"https://doi.org/10.1287/ijoc.2022.0344","url":null,"abstract":"INFORMS Journal on Computing, Ahead of Print. <br/>","PeriodicalId":13620,"journal":{"name":"Informs Journal on Computing","volume":"204 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2023-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138824414","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Correlation Clustering Problem Under Mediation","authors":"Zacharie Ales, Céline Engelbeen, Rosa Figueiredo","doi":"10.1287/ijoc.2022.0129","DOIUrl":"https://doi.org/10.1287/ijoc.2022.0129","url":null,"abstract":"INFORMS Journal on Computing, Ahead of Print. <br/>","PeriodicalId":13620,"journal":{"name":"Informs Journal on Computing","volume":"15 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2023-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138742959","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pietro D’Alessandro, Manlio Gaudioso, Giovanni Giallombardo, Giovanna Miglionico
INFORMS Journal on Computing, Ahead of Print.
INFORMS 计算期刊》，印刷版。
{"title":"The Descent–Ascent Algorithm for DC Programming","authors":"Pietro D’Alessandro, Manlio Gaudioso, Giovanni Giallombardo, Giovanna Miglionico","doi":"10.1287/ijoc.2023.0142","DOIUrl":"https://doi.org/10.1287/ijoc.2023.0142","url":null,"abstract":"INFORMS Journal on Computing, Ahead of Print. <br/>","PeriodicalId":13620,"journal":{"name":"Informs Journal on Computing","volume":"2 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2023-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138692616","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Heuristic Search for Rank Aggregation with Application to Label Ranking","authors":"Yangming Zhou, Jin-Kao Hao, Zhen Li, Fred Glover","doi":"10.1287/ijoc.2022.0019","DOIUrl":"https://doi.org/10.1287/ijoc.2022.0019","url":null,"abstract":"INFORMS Journal on Computing, Ahead of Print. <br/>","PeriodicalId":13620,"journal":{"name":"Informs Journal on Computing","volume":"36 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2023-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138692415","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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