Optimization of Logistics Systems Using Industry 4.0 Technologies

Dear Colleagues,

As a result of striving to meet individual customer needs, the complexity of the operation of logistics systems increases. For this reason, the improvement and optimization of various logistics processes is an increasing challenge for today's logistics professionals. The application of the new industry 4.0 technologies (e.g. cyber physics systems, big data, IoT, etc.) in logistics systems opens up many possibilities, including the collection and processing of system data, as well as the control of system components. This serves as the basis for new operating models, the development of which can reduce the losses of logistics systems and increase their sustainability. The main purpose of this special issue is to present new operating models in the field of logistics that have been developed and/or implemented using industry 4.0 technologies and optimization methods.

Suggested literature:

Spanos, A. C., Ponis, S. T., Tatsiopoulos, I. P., Christou, I. T., & Rokou, E. (2014). A new hybrid parallel genetic algorithm for the job‐shop scheduling problem. International Transactions in Operational Research, 21(3), 479-499.

Bányai, T.; Tamás, P.; Illés, B.; Stankevičiūtė, Ž.; Bányai, Á. Optimization of Municipal Waste Collection Routing: Impact of Industry 4.0 Technologies on Environmental Awareness and Sustainability. Int. J. Environ. Res. Public Health 2019, 16, 634.

Tamás P, Tollár S, Illés B, Bányai T, Tóth ÁB, Skapinyecz R. Decision Support Simulation Method for Process Improvement of Electronic Product Testing Systems. Sustainability. 2020; 12(7):3063.

Tamás P. Innovative Business Model for Realization of Sustainable Supply Chain at the Outsourcing Examination of Logistics Services. Sustainability. 2018; 10(1):210.

Ponis, S. T., & Koronis, E. (2012). Supply Chain Resilience? Definition of concept and its formative elements. The Journal of Applied Business Research, 28(5), 921-935.

Tamás P., Illés B. (2016) Process Improvement Trends for Manufacturing Systems in Industry 4.0., Academic Journal of Manufacturing Engineering, 119-124.

Ponis, S. T., Papanikolaou, P. A., Katimertzoglou, P., Ntalla, A. C., & Xenos, K. I. (2017). Household food waste in Greece: A questionnaire survey. Journal of Cleaner Production, 149, 1268-1277.

Ponis, S. T., & Efthymiou, O. K. (2020). Cloud and IoT Applications in Material Handling Automation and Intralogistics. Logistics, 4(3), 22.

Ponis, S. T. (2020). A Proposed Technology IoT Based Ecosystem for Tackling the Marine Beach Litter Problem. In Proceedings of SAI Intelligent Systems Conference (pp. 673-678). Springer, Cham.

Dr. Péter Tamás
Prof. Dr. Stavros T. Ponis
Guest Editors

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