Pub Date : 2017-09-01DOI: 10.1109/SOLI.2017.8121002
S. Digiesi, M. P. Fanti, G. Mummolo, B. Silvestri
In this paper a review of recent contributions in scientific literature on the last mile logistics is presented. The increase in freight transport and the actual growing trends are responsible, in the urban areas, of a critical increase of congestion, air pollution, noise and others externalities that involve the major cities in the world. New technologies and organizational strategies allow handling in a more efficient way the last mile delivery in urban areas. Papers that contribute significantly and with original proposal in reducing externalities in urban logistics are analysed in this work.
{"title":"Externalities reduction strategies in last mile logistics: A review","authors":"S. Digiesi, M. P. Fanti, G. Mummolo, B. Silvestri","doi":"10.1109/SOLI.2017.8121002","DOIUrl":"https://doi.org/10.1109/SOLI.2017.8121002","url":null,"abstract":"In this paper a review of recent contributions in scientific literature on the last mile logistics is presented. The increase in freight transport and the actual growing trends are responsible, in the urban areas, of a critical increase of congestion, air pollution, noise and others externalities that involve the major cities in the world. New technologies and organizational strategies allow handling in a more efficient way the last mile delivery in urban areas. Papers that contribute significantly and with original proposal in reducing externalities in urban logistics are analysed in this work.","PeriodicalId":190544,"journal":{"name":"2017 IEEE International Conference on Service Operations and Logistics, and Informatics (SOLI)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125359064","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}
Pub Date : 1900-01-01DOI: 10.1109/SOLI.2017.8120987
F. Nucci
In this paper, we study the single-vehicle routing problem (VRP) with time windows, multi-shift, and fuzzy uncertainty. In this problem, one vehicle is used repeatedly to serve demand over a planning horizon of several days. The problem is inspired by a routing problem in maintenance activities, where one maintenance crew uses a vehicle to perform jobs in various locations. Crew operates in shifts and always returns to depot before shift ends (no overtime is allowed). The objective consists in completing all the maintenance jobs in various locations minimizing the number of shifts the crew is used, and reducing the shift duration time. We study the effect of uncertainty in travel and job processing time on KPI. We develop an Artificial Immune Heuristic to solve the addressed problem. A numerical real test study is performed in order to investigate the problem. We propose a framework to evaluate the uncertainty effect. Results show important time saving can be obtained with the proposed approach.
{"title":"The multi-shift single-vehicle routing problem under fuzzy uncertainty","authors":"F. Nucci","doi":"10.1109/SOLI.2017.8120987","DOIUrl":"https://doi.org/10.1109/SOLI.2017.8120987","url":null,"abstract":"In this paper, we study the single-vehicle routing problem (VRP) with time windows, multi-shift, and fuzzy uncertainty. In this problem, one vehicle is used repeatedly to serve demand over a planning horizon of several days. The problem is inspired by a routing problem in maintenance activities, where one maintenance crew uses a vehicle to perform jobs in various locations. Crew operates in shifts and always returns to depot before shift ends (no overtime is allowed). The objective consists in completing all the maintenance jobs in various locations minimizing the number of shifts the crew is used, and reducing the shift duration time. We study the effect of uncertainty in travel and job processing time on KPI. We develop an Artificial Immune Heuristic to solve the addressed problem. A numerical real test study is performed in order to investigate the problem. We propose a framework to evaluate the uncertainty effect. Results show important time saving can be obtained with the proposed approach.","PeriodicalId":190544,"journal":{"name":"2017 IEEE International Conference on Service Operations and Logistics, and Informatics (SOLI)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123892202","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}
Pub Date : 1900-01-01DOI: 10.1109/SOLI.2017.8120992
J. Ferreira, V. Monteiro, J. Afonso, A. Martins, J. Afonso
This paper presents a low cost mobile application (app) integrated on an Internet of Things (IoT) ecosystem, which uses varied sensor information collected by mobile devices to track and assist on the logistics of urban goods distribution processes. The proposed approach is leveraged by the trend of decreasing costs for mobile data communication in urban environments. Taking into account basic sensor data available in mobile devices (e.g., GPS, accelerometer and magnetometer), it is possible to track the users' movements and adopted routes, identify transit times and driving styles, identify the quality of roads, and track the process of loading/unloading of urban goods. This data can also be analyzed through a data mining process to identify patterns, present driving advice and perform a resource optimization process.
{"title":"Mobile device sensing system for urban goods distribution logistics","authors":"J. Ferreira, V. Monteiro, J. Afonso, A. Martins, J. Afonso","doi":"10.1109/SOLI.2017.8120992","DOIUrl":"https://doi.org/10.1109/SOLI.2017.8120992","url":null,"abstract":"This paper presents a low cost mobile application (app) integrated on an Internet of Things (IoT) ecosystem, which uses varied sensor information collected by mobile devices to track and assist on the logistics of urban goods distribution processes. The proposed approach is leveraged by the trend of decreasing costs for mobile data communication in urban environments. Taking into account basic sensor data available in mobile devices (e.g., GPS, accelerometer and magnetometer), it is possible to track the users' movements and adopted routes, identify transit times and driving styles, identify the quality of roads, and track the process of loading/unloading of urban goods. This data can also be analyzed through a data mining process to identify patterns, present driving advice and perform a resource optimization process.","PeriodicalId":190544,"journal":{"name":"2017 IEEE International Conference on Service Operations and Logistics, and Informatics (SOLI)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127549584","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}
Pub Date : 1900-01-01DOI: 10.1109/SOLI.2017.8120995
S. Monteleone, Mauro Sampaio, R. Maia
Temperature monitoring of medicines is essential for product quality and patient safety. Product quality is influenced by temperature perturbations and time delays in interventions. Thanks to Internet of Things (IoT) considerable progress has been made in recent years in the improvement of temperature monitoring devices. However, temperature monitoring in medicine Cold Chain remains challenging. In this paper it is presented a conceptual model aiming at overcoming challenges of medicine Cold Chain related to temperature monitoring. The major particularity of our model is that it considers the complete Cold Chain according to two perspectives of pharmaceutical and healthcare industries in a single study. Besides this model can be applied also in vaccine Cold Chain and in temperature-controlled logistics of laboratory medicine. Our conceptual model supports the development of a smart Cold Chain system for temperature monitoring based on IoT. Our smart Cold Chain system can be used to improve Cold Chain responsiveness by studying weaknesses and deciding what Cold Chain characteristics to improve.
{"title":"A novel deployment of smart Cold Chain system using 2G-RFID-Sys temperature monitoring in medicine Cold Chain based on Internet of Things","authors":"S. Monteleone, Mauro Sampaio, R. Maia","doi":"10.1109/SOLI.2017.8120995","DOIUrl":"https://doi.org/10.1109/SOLI.2017.8120995","url":null,"abstract":"Temperature monitoring of medicines is essential for product quality and patient safety. Product quality is influenced by temperature perturbations and time delays in interventions. Thanks to Internet of Things (IoT) considerable progress has been made in recent years in the improvement of temperature monitoring devices. However, temperature monitoring in medicine Cold Chain remains challenging. In this paper it is presented a conceptual model aiming at overcoming challenges of medicine Cold Chain related to temperature monitoring. The major particularity of our model is that it considers the complete Cold Chain according to two perspectives of pharmaceutical and healthcare industries in a single study. Besides this model can be applied also in vaccine Cold Chain and in temperature-controlled logistics of laboratory medicine. Our conceptual model supports the development of a smart Cold Chain system for temperature monitoring based on IoT. Our smart Cold Chain system can be used to improve Cold Chain responsiveness by studying weaknesses and deciding what Cold Chain characteristics to improve.","PeriodicalId":190544,"journal":{"name":"2017 IEEE International Conference on Service Operations and Logistics, and Informatics (SOLI)","volume":"479 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123228375","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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