Infor最新文献

{"title":"Production-and-order strategy with demand information updating and uncertain spot price","authors":"Jiawu Peng, Honglin Yang, Hong Wan","doi":"10.1080/03155986.2024.2327760","DOIUrl":"https://doi.org/10.1080/03155986.2024.2327760","url":null,"abstract":"We study production-and-order strategy in a two-echelon supply chain consisting of a single manufacturer and a single retailer in which both market demand and spot price are uncertain. The retailer...","PeriodicalId":13645,"journal":{"name":"Infor","volume":"59 1","pages":""},"PeriodicalIF":1.3,"publicationDate":"2024-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140203500","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":"Enhancing logistics performance measurement: an effectiveness-based hierarchical data envelopment analysis approach","authors":"Kok Fong See, Yongli Guo, Ming-Miin Yu","doi":"10.1080/03155986.2024.2309420","DOIUrl":"https://doi.org/10.1080/03155986.2024.2309420","url":null,"abstract":"The logistics performance index (LPI) is a comprehensive and comparable composite index developed by the World Bank to assess a country’s logistics and trade facilitation environment. However, the ...","PeriodicalId":13645,"journal":{"name":"Infor","volume":"24 1","pages":""},"PeriodicalIF":1.3,"publicationDate":"2024-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140151067","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":"Real-time production scheduling using a deep reinforcement learning-based multi-agent approach","authors":"Sharareh Taghipour, Hamed A. Namoura, Mani Sharifi, Mageed Ghaleb","doi":"10.1080/03155986.2023.2287996","DOIUrl":"https://doi.org/10.1080/03155986.2023.2287996","url":null,"abstract":"In the real-time scheduling (RTS) research field, it has been shown that employing multiple dispatching rules (MDRs) for the components in a flexible manufacturing system will improve production pe...","PeriodicalId":13645,"journal":{"name":"Infor","volume":"76 1","pages":""},"PeriodicalIF":1.3,"publicationDate":"2024-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140034312","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":"An approach to plan infrastructural investments to facilitate domestic trade","authors":"Osman Alp, Meraj Ajam","doi":"10.1080/03155986.2024.2311472","DOIUrl":"https://doi.org/10.1080/03155986.2024.2311472","url":null,"abstract":"The volume of trade between two regions is shaped by the cost of trade, which is a function of infrastructural and political barriers. Governments can invest in the upgrade of their country’s logis...","PeriodicalId":13645,"journal":{"name":"Infor","volume":"8 1","pages":""},"PeriodicalIF":1.3,"publicationDate":"2024-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139771940","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":"Intra-provincial benchmark analysis of COVID-19 in Canada","authors":"Mehmet A. Begen, Fredrik Ødegaard, Jafar Sadeghi","doi":"10.1080/03155986.2024.2302298","DOIUrl":"https://doi.org/10.1080/03155986.2024.2302298","url":null,"abstract":"The COVID-19 pandemic posed unheralded challenges to people, business, government at all levels (federal, provincial, regional), and society at large. In addition to the direct consequences of taki...","PeriodicalId":13645,"journal":{"name":"Infor","volume":"2 2 1","pages":""},"PeriodicalIF":1.3,"publicationDate":"2024-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139463119","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":"Data-driven fair resource allocation for novel emerging epidemics: a COVID-19 Convalescent Plasma case study","authors":"Maryam Akbari-Moghaddam, Na Li, Douglas G. Down, Donald M. Arnold, Jeannie Callum, Philippe Bégin, Nancy M. Heddle","doi":"10.1080/03155986.2023.2264985","DOIUrl":"https://doi.org/10.1080/03155986.2023.2264985","url":null,"abstract":"AbstractEpidemics are a serious public health threat, and the resources for mitigating their effects are typically limited. Decision-makers face challenges in forecasting the supply and demand for these resources as prior information about the disease is often not available, the behaviour of the disease can periodically change (either naturally or as a result of public health policies) and can differ by geographical region. In this work, we discuss a model that is suitable for short-term real-time supply and demand forecasting during emerging outbreaks. We consider a case study of demand forecasting and allocating scarce quantities of COVID-19 Convalescent Plasma (CCP) in an international multi-site Randomized Controlled Trial (RCT) involving multiple hospital hubs across Canada (excluding Québec). We propose a data-driven mixed-integer programming (MIP) resource allocation model that assigns available resources to maximize a notion of fairness among the resource-demanding entities. Numerical results from applying our MIP model to the case study suggest that our approach can help balance the supply and demand of limited products such as CCP and minimize the unmet demand ratios of the demand entities. We analyse the sensitivity of our model to different allocation settings and show that our model assigns equitable allocations across the entities.Keywords: Resource allocationepidemicsCOVID-19 Convalescent Plasmadata-driven optimizationdemand forecasting AcknowledgmentsThe authors would like to thank Julie Carruthers, Erin Jamula, and Melanie St John at the McMaster Centre for Transfusion Research for their administrative support.Disclosure statementNo potential conflict of interest was reported by the author(s).Data availability statementDue to the ethically, legally, and commercially sensitive nature of the research, participants of this study did not agree for their data to be shared publicly, so supporting data is not available.Additional informationFundingThis work was supported by Mitacs Research Training Award (Award IT22358), the McMaster Centre for Transfusion Research, and the Natural Sciences and Engineering Research Council of Canada (NSERC) Discovery Grant Program (RGPIN-2016-04518 and RGPIN-2022-02999).","PeriodicalId":13645,"journal":{"name":"Infor","volume":"102 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135302594","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":"Markov chain Monte Carlo approach to the analysis of response patterns in data collection process","authors":"Y. H. Chun, E. Watson","doi":"10.1080/03155986.2023.2245304","DOIUrl":"https://doi.org/10.1080/03155986.2023.2245304","url":null,"abstract":"Abstract Survey research, such as telephone, mail, or online questionnaires, is one of the most widely used tools for collecting sample data. We are often interested in the total number of replies that would be received during a given time period. Many researchers have developed a wide variety of curve-fitting methods to predict the response rate of recipients over time. However, previous models are based on some assumptions that are hardly justified in practice. In this paper, a new response model is proposed that is based on meaningful parameters such as the ultimate response rate of questionnaire recipients, delay rate of respondents, and average delivery time of responses. To estimate those model parameters, we use the Markov chain Monte Carlo (MCMC) method, which is increasingly popular in the operational research community. With mail survey data in marketing research, we test our Bayesian response model and compare its performance with those of traditional curve-fitting models.","PeriodicalId":13645,"journal":{"name":"Infor","volume":"51 1","pages":""},"PeriodicalIF":1.3,"publicationDate":"2023-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78184832","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":"Mathematical formulations for multi-period network design with modular capacity adjustments","authors":"Warley Almeida Silva, S. D. Jena, Karan Jeswani","doi":"10.1080/03155986.2023.2229208","DOIUrl":"https://doi.org/10.1080/03155986.2023.2229208","url":null,"abstract":"Abstract Network design problems are at the heart of several applications in domains such as transportation, telecommunication, energy and natural resources. This paper proposes a new multi-period network design problem variant, in which modular capacities can be added or reduced along the planning horizon in order to adapt to demand changes. The problem further allows to represent economies of scales in function of the total arc capacity, a detail that has typically been overlooked in the literature. This paper particularly emphasizes the different alternatives to formulate the problem. We propose two different mixed-integer programming formulations and analyze further modeling alternatives. We theoretically compare the strength of all formulations and evaluate their computational performance in extensive experiments. The results suggest that a recent modeling technique using more precise decision variables yields the strongest formulation, which also results in significantly faster solution times. The use of this formulation may therefore be beneficial when considering similar problem variants. Finally, we also evaluate the economical benefits of the features introduced in this new problem variant, indicating that both the selection of the capacity levels and the capacity adjustment along time are likely to result in significant cost savings.","PeriodicalId":13645,"journal":{"name":"Infor","volume":"77 1","pages":""},"PeriodicalIF":1.3,"publicationDate":"2023-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81912384","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":"A reinforcement learning based dynamic room pricing model for hotel industry","authors":"Gamze Tuncay, Kıymet Kaya, Yaren Yilmaz, Y. Yaslan, Şule Gündüz Öğüdücü","doi":"10.1080/03155986.2023.2235223","DOIUrl":"https://doi.org/10.1080/03155986.2023.2235223","url":null,"abstract":"","PeriodicalId":13645,"journal":{"name":"Infor","volume":"1 1","pages":""},"PeriodicalIF":1.3,"publicationDate":"2023-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85331389","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":"The impact of time aggregation and travel time models on time-dependent routing solutions","authors":"R. Jaballah, Rodrigo Ramalho, J. Renaud, Leandro C. Coelho","doi":"10.1080/03155986.2023.2229603","DOIUrl":"https://doi.org/10.1080/03155986.2023.2229603","url":null,"abstract":"Abstract Traffic and congestion have a big impact on the performance of transportation systems. Travel time models are required to calculate trip durations and arrival times when traffic information is available. These models rely on the availability of detailed information about the traffic state. With the growing availability of onboard devices, we can now capture very precise data with a very high frequency. The challenge is now to efficiently use these data to solve routing problems and evaluate routing solutions. A key question that emerges is how to determine the best compromise between a huge amount of very precise data and a smaller volume of aggregated data. In this article, we analyze the impact of time aggregation on the performance of the main travel time models, namely the link travel model (LTM), the flow speed model (FSM) and the smoothed travel time model (STTM). We also analyze the impact of different time aggregation levels on these models. Our results show that all models share similar performance, particularly with large intervals. Finally, we show that the LTM largely respects the FIFO property, which is an important hypothesis for routing algorithms.","PeriodicalId":13645,"journal":{"name":"Infor","volume":"100 6 1","pages":""},"PeriodicalIF":1.3,"publicationDate":"2023-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87728618","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}