Planning and Operation of Interconnected Intelligent Logistics Systems

A special issue of Logistics (ISSN 2305-6290). This special issue belongs to the section "Artificial Intelligence, Logistics Analytics, and Automation".

Deadline for manuscript submissions: closed (15 June 2018) | Viewed by 11536

Special Issue Editors

Institute of Logistics, University of Miskolc, 3515 Miskolc-Egyetemváros, Hungary
Interests: transportation; supply chain; city logistics; optimization; logistics; Industry 4.0; intelligent transportation systems
Special Issues, Collections and Topics in MDPI journals
Centre de Gestion Scientifique, MINES ParisTech, PSL-Research University, 75272 Paris, France
Interests: sustainable logistics; physical internet; smart city logistics; freight transportation; operations management

Special Issue Information

Dear Colleagues,

Supply chains have become more and more complex because of the increasing diversity of customer demands. The state-of-the-art technologies in a variety of engineering disciplines, information sciences and computational engineering necessitate building physical and logical linkages among different supply chains to create additional flexibility and plasticity enabled by the hyperconnected resources. As a result, the separated supply chain structure is underlying a transition to an interconnected intelligent logistics system, for example, the Physical Internet (Ballot et al. 2014, Pan et al. 2017), Intelligent logistics (McFarlane et al. 2016, Sallez et al. 2016), or hyperconnected logistics (Crainic and Montreuil 2016). During this transition, there are many technical and economic challenges to be addressed, such as system planning, operation management, IT integration, business model, which require interdisciplinary research (Bányai et al. 2017). The optimal design and operation of interconnected intelligent logistics systems can led to increased efficiency, traceability, utilization, availability and capability while operation cost and ecological footprint is decreased.

We invite researchers in the global logistics community to contribute original research papers, as well as review articles and empirical studies, which will stimulate debate in the topic.

Potential topics include, but are not limited to, the following:

  • analytic and heuristic optimisation of supply chain and interconnected intelligent logistics systems;
  • simulation of large scale interconnected intelligent logistics systems,
  • decision-making in networking logistics,
  • information management in large scale logistic systems,
  • Industry 4.0, smart manufacturing and Made in China 2025 from the aspect of interconnected intelligent logistics systems,
  • business models in cooperative logistic solutions,
  • application of intelligent sensor networks in coordination of large scale supply chain,
  • new engineering solutions in interconnected intelligent logistics.
  • interconnected intelligent logistics for sustainability

References

Ballot, E., B. Montreuil and R. Meller (2014). The Physical Internet: The Network of Logistics Networks. Paris, France, La documentation Française. 978-2-11-009865-8

Bányai Á., Bányai T., Illés B. (2017). "Optimization of consignment store based supply chain with black hole algorithm." Complexity. Paper 6038973. http://dx.doi.org/10.1155/2017/6038973.

Crainic, T. G. and B. Montreuil (2016). "Physical Internet Enabled Hyperconnected City Logistics." Transportation Research Procedia 12: 383-398. DOI: http://dx.doi.org/10.1016/j.trpro.2016.02.074.

McFarlane, D., V. Giannikas and W. Lu (2016). "Intelligent logistics: Involving the customer." Computers in Industry 81: 105-115. DOI: http://dx.doi.org/10.1016/j.compind.2015.10.002.

Pan, S., E. Ballot, G. Q. Huang and B. Montreuil (2017). "Physical Internet and interconnected logistics services: research and applications." International Journal of Production Research 55(9): 2603-2609. DOI: http://dx.doi.org/10.1080/00207543.2017.1302620.

Sallez, Y., S. Pan, B. Montreuil, T. Berger and E. Ballot (2016). "On the activeness of intelligent Physical Internet containers." Computers in Industry 81: 96-104. DOI: http://dx.doi.org/10.1016/j.compind.2015.12.006.

Dr. Tamás Bányai
Dr. Shenle Pan
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Logistics is an international peer-reviewed open access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • analytic and heuristic optimisation of supply chain and interconnected intelligent logistics systems;
  • simulation of large scale interconnected intelligent logistics systems,
  • decision-making in networking logistics,
  • information management in large scale logistic systems,
  • Industry 4.0, smart manufacturing and Made in China 2025 from the aspect of interconnected intelligent logistics systems,
  • business models in cooperative logistic solutions,
  • application of intelligent sensor networks in coordination of large scale supply chain,
  • new engineering solutions in interconnected intelligent logistics.
  • interconnected intelligent logistics for sustainability

Published Papers (2 papers)

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Research

32 pages, 8336 KiB  
Article
Towards a Business Model Framework to Increase Collaboration in the Freight Industry
by Alix Vargas, Shushma Patel and Dilip Patel
Logistics 2018, 2(4), 22; https://doi.org/10.3390/logistics2040022 - 09 Oct 2018
Cited by 15 | Viewed by 7656
Abstract
Collaboration in the freight industry has not been widely adopted mainly due to the perceived barriers in competition resulting in a lack of trust among fleet operators. Collaboration in this sector has significant benefits, including the reduction of empty running, operating costs (OPEX) [...] Read more.
Collaboration in the freight industry has not been widely adopted mainly due to the perceived barriers in competition resulting in a lack of trust among fleet operators. Collaboration in this sector has significant benefits, including the reduction of empty running, operating costs (OPEX) and greenhouse gas emissions (GHG) resulting in greater utilisation of existing logistics assets. A review of the literature to establish the critical aspects of freight collaboration was undertaken, as well as analyses of published case studies and European Union (EU)-funded projects. The critical aspects and barriers identified include: revenue sharing; compliance with competition law; process synchronization; organisational and systems interoperability; different forms of collaboration from a physical and coordination structure perspective; and strategies for collaboration. To facilitate collaboration a freight collaborative business model (FCBM) framework that highlights problematic areas in freight collaboration is proposed to support standardizing collaborative practices in the freight industry. Three published freight industry collaboration business cases were evaluated against the model. The business model framework is intended as a tool to be used to compare different business models and identify the best innovations to help facilitate collaborative practices. The freight collaboration business model was applied to the Freight Share Lab research project in order to demonstrate the concept and investigate whether efficiency can be unlocked through deployment of a dynamic data and asset sharing platform to enable route and load optimization across multiple fleets of freight vehicles, rail freight wagons and containers. Full article
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11 pages, 999 KiB  
Article
Scheduling Approach for the Simulation of a Sustainable Resource Supply Chain
by Henning Strubelt, Sebastian Trojahn, Sebastian Lang and Abdulrahman Nahhas
Logistics 2018, 2(3), 12; https://doi.org/10.3390/logistics2030012 - 16 Jul 2018
Cited by 1 | Viewed by 2870
Abstract
The general goal of waste management is to conserve resources and avoid negative environmental impacts. This paper deals with the optimization of logistics processes at an underground waste storage site by means of solving scheduling issues and reducing setup times, with the help [...] Read more.
The general goal of waste management is to conserve resources and avoid negative environmental impacts. This paper deals with the optimization of logistics processes at an underground waste storage site by means of solving scheduling issues and reducing setup times, with the help of a simulation model. Specific to underground waste storage is the fact that it is often only a side business to actual mining. With limited capacity and resources, all legal requirements must be met, while the business should still be profitable. This paper discusses the improvement of a logistical system’s performance using machine scheduling approaches with the support of a plant simulation model. The process sequence is determined by means of a priority index. Genetic algorithms are then applied to improve the priority index to further increase performance. Results of the simulation model show that the performance of the logistics system can be increased by up to 400 percent, ensuring adequate system performance for current as well as future demand without changes to the system’s capacities and resources. Full article
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