{"title":"Demand side perception: The mediating role of public procurement regulatory framework in successful road construction implementation","authors":"Noah Mwelu, Susan Watundu, M. Moya","doi":"10.23773/2023_2","DOIUrl":"https://doi.org/10.23773/2023_2","url":null,"abstract":"","PeriodicalId":49772,"journal":{"name":"Naval Research Logistics","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84952666","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Parcel delivery systems for city logistics: a cost-based comparison between different transportation technologies","authors":"B. Himstedt, F. Meisel","doi":"10.23773/2023_3","DOIUrl":"https://doi.org/10.23773/2023_3","url":null,"abstract":"","PeriodicalId":49772,"journal":{"name":"Naval Research Logistics","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91070504","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Decentral decision-making for energy-aware charging of intralogistics equipment","authors":"S. Scholz","doi":"10.23773/2023_4","DOIUrl":"https://doi.org/10.23773/2023_4","url":null,"abstract":"","PeriodicalId":49772,"journal":{"name":"Naval Research Logistics","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81911935","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Automated Trucks and the Future of Logistics - A Delphi-Based Scenario Study","authors":"Svenja Escherle, Emilia Darlagiannis, Anna Sprung","doi":"10.23773/2023_1","DOIUrl":"https://doi.org/10.23773/2023_1","url":null,"abstract":"","PeriodicalId":49772,"journal":{"name":"Naval Research Logistics","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74661219","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-03-01Epub Date: 2021-06-11DOI: 10.1002/nav.22007
Dimitris Bertsimas, Vassilis Digalakis, Alexander Jacquillat, Michael Lingzhi Li, Alessandro Previero
The outbreak of COVID-19 led to a record-breaking race to develop a vaccine. However, the limited vaccine capacity creates another massive challenge: how to distribute vaccines to mitigate the near-end impact of the pandemic? In the United States in particular, the new Biden administration is launching mass vaccination sites across the country, raising the obvious question of where to locate these clinics to maximize the effectiveness of the vaccination campaign. This paper tackles this question with a novel data-driven approach to optimize COVID-19 vaccine distribution. We first augment a state-of-the-art epidemiological model, called DELPHI, to capture the effects of vaccinations and the variability in mortality rates across age groups. We then integrate this predictive model into a prescriptive model to optimize the location of vaccination sites and subsequent vaccine allocation. The model is formulated as a bilinear, nonconvex optimization model. To solve it, we propose a coordinate descent algorithm that iterates between optimizing vaccine distribution and simulating the dynamics of the pandemic. As compared to benchmarks based on demographic and epidemiological information, the proposed optimization approach increases the effectiveness of the vaccination campaign by an estimated 20%, saving an extra 4000 extra lives in the United States over a 3-month period. The proposed solution achieves critical fairness objectives-by reducing the death toll of the pandemic in several states without hurting others-and is highly robust to uncertainties and forecast errors-by achieving similar benefits under a vast range of perturbations.
{"title":"Where to locate COVID-19 mass vaccination facilities?","authors":"Dimitris Bertsimas, Vassilis Digalakis, Alexander Jacquillat, Michael Lingzhi Li, Alessandro Previero","doi":"10.1002/nav.22007","DOIUrl":"10.1002/nav.22007","url":null,"abstract":"<p><p>The outbreak of COVID-19 led to a record-breaking race to develop a vaccine. However, the limited vaccine capacity creates another massive challenge: how to distribute vaccines to mitigate the near-end impact of the pandemic? In the United States in particular, the new Biden administration is launching mass vaccination sites across the country, raising the obvious question of where to locate these clinics to maximize the effectiveness of the vaccination campaign. This paper tackles this question with a novel data-driven approach to optimize COVID-19 vaccine distribution. We first augment a state-of-the-art epidemiological model, called DELPHI, to capture the effects of vaccinations and the variability in mortality rates across age groups. We then integrate this predictive model into a prescriptive model to optimize the location of vaccination sites and subsequent vaccine allocation. The model is formulated as a bilinear, nonconvex optimization model. To solve it, we propose a coordinate descent algorithm that iterates between optimizing vaccine distribution and simulating the dynamics of the pandemic. As compared to benchmarks based on demographic and epidemiological information, the proposed optimization approach increases the effectiveness of the vaccination campaign by an estimated 20%, saving an extra 4000 extra lives in the United States over a 3-month period. The proposed solution achieves critical fairness objectives-by reducing the death toll of the pandemic in several states without hurting others-and is highly robust to uncertainties and forecast errors-by achieving similar benefits under a vast range of perturbations.</p>","PeriodicalId":49772,"journal":{"name":"Naval Research Logistics","volume":null,"pages":null},"PeriodicalIF":1.9,"publicationDate":"2022-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8441649/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49412464","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-02-01Epub Date: 2021-03-16DOI: 10.1002/nav.21985
Hussein El Hajj, Douglas R Bish, Ebru K Bish, Hrayer Aprahamian
Testing provides essential information for managing infectious disease outbreaks, such as the COVID-19 pandemic. When testing resources are scarce, an important managerial decision is who to test. This decision is compounded by the fact that potential testing subjects are heterogeneous in multiple dimensions that are important to consider, including their likelihood of being disease-positive, and how much potential harm would be averted through testing and the subsequent interventions. To increase testing coverage, pooled testing can be utilized, but this comes at a cost of increased false-negatives when the test is imperfect. Then, the decision problem is to partition the heterogeneous testing population into three mutually exclusive sets: those to be individually tested, those to be pool tested, and those not to be tested. Additionally, the subjects to be pool tested must be further partitioned into testing pools, potentially containing different numbers of subjects. The objectives include the minimization of harm (through detection and mitigation) or maximization of testing coverage. We develop data-driven optimization models and algorithms to design pooled testing strategies, and show, via a COVID-19 contact tracing case study, that the proposed testing strategies can substantially outperform the current practice used for COVID-19 contact tracing (individually testing those contacts with symptoms). Our results demonstrate the substantial benefits of optimizing the testing design, while considering the multiple dimensions of population heterogeneity and the limited testing capacity.
{"title":"Screening multi-dimensional heterogeneous populations for infectious diseases under scarce testing resources, with application to COVID-19.","authors":"Hussein El Hajj, Douglas R Bish, Ebru K Bish, Hrayer Aprahamian","doi":"10.1002/nav.21985","DOIUrl":"10.1002/nav.21985","url":null,"abstract":"<p><p>Testing provides essential information for managing infectious disease outbreaks, such as the COVID-19 pandemic. When testing resources are scarce, an important managerial decision is who to test. This decision is compounded by the fact that potential testing subjects are heterogeneous in multiple dimensions that are important to consider, including their likelihood of being disease-positive, and how much potential harm would be averted through testing and the subsequent interventions. To increase testing coverage, pooled testing can be utilized, but this comes at a cost of increased false-negatives when the test is imperfect. Then, the decision problem is to partition the heterogeneous testing population into three mutually exclusive sets: those to be individually tested, those to be pool tested, and those not to be tested. Additionally, the subjects to be pool tested must be further partitioned into testing pools, potentially containing different numbers of subjects. The objectives include the minimization of harm (through detection and mitigation) or maximization of testing coverage. We develop data-driven optimization models and algorithms to design pooled testing strategies, and show, via a COVID-19 contact tracing case study, that the proposed testing strategies can substantially outperform the current practice used for COVID-19 contact tracing (individually testing those contacts with symptoms). Our results demonstrate the substantial benefits of optimizing the testing design, while considering the multiple dimensions of population heterogeneity and the limited testing capacity.</p>","PeriodicalId":49772,"journal":{"name":"Naval Research Logistics","volume":null,"pages":null},"PeriodicalIF":1.9,"publicationDate":"2022-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8251476/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42640282","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Deike Gliem, U. Jessen, S. Wenzel, Wibke Kusturica, C. Laroque
{"title":"Ontology-based Forecast of the Duration of Logistics Processes in One-of-a-Kind Production in SME","authors":"Deike Gliem, U. Jessen, S. Wenzel, Wibke Kusturica, C. Laroque","doi":"10.23773/2022_5","DOIUrl":"https://doi.org/10.23773/2022_5","url":null,"abstract":"","PeriodicalId":49772,"journal":{"name":"Naval Research Logistics","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82435025","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Stephan L. K. Freichel, Johannes K. Wörtge, Arthur Haas, L. T. Veer
{"title":"Cargo Accumulation Risks in Maritime Supply Chains: A new perspective towards Risk Management for Theory, and Recommendations for the Insurance Industry and Cargo Shippers","authors":"Stephan L. K. Freichel, Johannes K. Wörtge, Arthur Haas, L. T. Veer","doi":"10.23773/2022_4","DOIUrl":"https://doi.org/10.23773/2022_4","url":null,"abstract":"","PeriodicalId":49772,"journal":{"name":"Naval Research Logistics","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83679830","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The continuous increase in technology associated with the Fourth Industrial Revolution and advancing digitalization are influencing today’s production processes and the competitiveness of factories. Integrating Industry 4.0 into Lean Production can generate more efficient, leaner production and logistics with the help of intelligent networking systems. However, combining the two concepts also poses some challenges, such as the complex integration of technology into the Lean Production tools, and a resistance from employees to accept new technological ways. Furthermore, there is a lack of practical studies that guide companies on which variant of the different Industry 4.0 technologies should and could be integrated into their Lean Production processes. This paper analyzes the compatibility of Industry 4.0 and Lean Production and presents practical solutions by highlighting the opportunities and challenges of combining the two. This research is based on a systematic literature analysis and evaluating expert interviews which leads to the findings and hypotheses. The results explain how Lean Production and Industry 4.0 can be successfully combined, and which aspects need to be and should be considered on a management level.
{"title":"Compatibility, opportunities and challenges in the combination of Industry 4.0 and Lean Production","authors":"Serdar Yürekli, Carola Schulz","doi":"10.23773/2022_9","DOIUrl":"https://doi.org/10.23773/2022_9","url":null,"abstract":"The continuous increase in technology associated with the Fourth Industrial Revolution and advancing digitalization are influencing today’s production processes and the competitiveness of factories. Integrating Industry 4.0 into Lean Production can generate more efficient, leaner production and logistics with the help of intelligent networking systems. However, combining the two concepts also poses some challenges, such as the complex integration of technology into the Lean Production tools, and a resistance from employees to accept new technological ways. Furthermore, there is a lack of practical studies that guide companies on which variant of the different Industry 4.0 technologies should and could be integrated into their Lean Production processes. This paper analyzes the compatibility of Industry 4.0 and Lean Production and presents practical solutions by highlighting the opportunities and challenges of combining the two. This research is based on a systematic literature analysis and evaluating expert interviews which leads to the findings and hypotheses. The results explain how Lean Production and Industry 4.0 can be successfully combined, and which aspects need to be and should be considered on a management level.","PeriodicalId":49772,"journal":{"name":"Naval Research Logistics","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87915518","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
扫码关注我们
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号