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Energies
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Sustainability and Energy Efficiency in Logistics
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Sustainability and Energy Efficiency in Logistics

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "F5: Artificial Intelligence and Smart Energy".

Deadline for manuscript submissions: closed (11 September 2023) | Viewed by 4698

Special Issue Editors

Prof. Dr. Mario Safran

E-Mail Website
Guest Editor
Faculty of Traffic Science, University of Zagreb, Zagreb, Croatia
Interests: transport and traffic sciences; logistics
Dr. Martin Gregurić

E-Mail Website
Guest Editor
Faculty of Transport and Traffic Sciences, University of Zagreb, Zagreb, Croatia
Interests: application of data science and AI in control and analysis of transport processes
Special Issues, Collections and Topics in MDPI journals
Dr. Dario Medić

E-Mail Website
Guest Editor
Faculty of Maritime Studies, University of Split, Split, Croatia
Interests: Search and rescue at sea; optimization of logistic processes in maritime transport; risk management in maritime transport

Special Issue Information

Dear Colleagues,

The logistics industry is facing new challenges in operating global supply chains due to the specific circumstances introduced by the COVID-19 pandemic. Increased transit time and a lack of transport capacity caused by more exhaustive border controls, closing or reducing the capacity of ports and terminals, labour shortages, etc. require more efficient and sustainable logistic solutions. Simultaneously, the ecological imperative makes it necessary to employ environmentally friendly equipment and technology in transport and logistics. It is well known that reducing energy consumption is one of the keys to reducing greenhouse gas emissions into the atmosphere, and the logistics industry emits a significant portion of these.

Research and review articles are therefore invited for submission to this Special Issue that are related, but not limited, to:

  • AI and data science for the optimization and analysis of logistics processes;
  • Possibility of reducing energy consumption by optimizing logistics processes;
  • Reduction of greenhouse gas emissions by introducing electric vehicles and other environmentally friendly equipment;
  • Process automation in warehouse logistics and transportation;
  • IoT solutions in transport, inventory, and warehouse management;
  • Improving competitiveness of transport and logistics services and raising customer satisfaction;
  • Sustainable supply chain solutions in terms of energy efficiency, environmental protection, working conditions, and social responsibility. 

Prof. Dr. Mario Safran
Dr. Martin Gregurić
Dr. Dario Medić
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. Energies is an international peer-reviewed open access semimonthly 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 2600 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

  • transport technology
  • energy efficiency
  • automation
  • logistic services
  • reverse logistic
  • IoT solutions
  • greenhouse gas emissions
  • supply chain
  • sustainability

Published Papers (2 papers)

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Research

20 pages, 2675 KiB  
Article
A Vehicle Routing Optimization Model for Community Group Buying Considering Carbon Emissions and Total Distribution Costs
by Zhiqiang Liu, Yanqi Niu, Caiyun Guo and Shitong Jia
Energies 2023, 16(2), 931; https://0-doi-org.brum.beds.ac.uk/10.3390/en16020931 - 13 Jan 2023
Cited by 5 | Viewed by 1680
Abstract
Under the background of the normalization of COVID-19 prevention and control and the rapid development of e-commerce, community group buying has occupied the market by providing low-priced, fast, and green consumer goods, but with it, the logistics and distribution volume of goods has [...] Read more.
Under the background of the normalization of COVID-19 prevention and control and the rapid development of e-commerce, community group buying has occupied the market by providing low-priced, fast, and green consumer goods, but with it, the logistics and distribution volume of goods has also increased sharply. In order to reduce environmental pollution and the carbon emissions caused by transportation in the community group buying logistics distribution, it is necessary to investigate a suitable method to optimize vehicle distribution routes and reduce carbon emissions. Taking the lowest total costs of logistics and distribution and the smallest carbon emissions, this article introduces soft time window function and carbon emissions parameters, takes the delivery of goods from the community group buying distribution center in Wu’an Town, Hebei Province to customer points in 14 townships as an example, an optimization model for the distribution route of low carbon vehicles for community group buying based on improved genetic algorithm was constructed, AHP-EW fusion technology was used to calculate carbon emissions and cost weights, and compared with the traditional genetic algorithm and ant colony algorithm two typical heuristic algorithms, the feasibility of the proposed model and the advantages of the improved algorithm are verified, and the research results showed that it can reduce the costs and carbon emissions of vehicle distribution, provide decision-making reference for community group buying logistics enterprise distribution, and promote energy conservation and environmental sustainable development. Full article
(This article belongs to the Special Issue Sustainability and Energy Efficiency in Logistics)
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14 pages, 3292 KiB  
Article
Saving Energy by Optimizing Warehouse Dock Door Allocation
by Ratko Stanković, Kristijan Rogić and Mario Šafran
Energies 2022, 15(16), 5862; https://0-doi-org.brum.beds.ac.uk/10.3390/en15165862 - 12 Aug 2022
Cited by 2 | Viewed by 1454
Abstract
As energy consumption constantly gains importance, it has become one of the major issues in managing logistics systems. However, it is ranked against other company priorities, and the rationalization for investing in energy needs to be justified by the savings achieved. A solution [...] Read more.
As energy consumption constantly gains importance, it has become one of the major issues in managing logistics systems. However, it is ranked against other company priorities, and the rationalization for investing in energy needs to be justified by the savings achieved. A solution for reducing energy consumption via electric forklifts for performing docking operations at distribution centers, which requires no investments in infrastructure or equipment, is outlined in this paper. The solution is based on optimizing inbound dock door allocation, and the energy savings are quantified using a simulation model. A case study of a local FMCG distributor’s logistics center was conducted to collect the data and information needed for modeling inbound docking operations and performing simulation experiments. The optimal dock door allocation was obtained using a linear programming method using an MS Excel spreadsheet optimizer (Solver), while the simulation of the docking operations was carried out using FlexSim simulation software. The experimental results show that the solution outlined in this paper enables savings in the electric energy consumption of forklifts of between 12.8% and 14.5%, compared to the empirical solution applied by the company in the case study. The intended contribution of this paper is not limited to presenting an applicable solution for energy savings in performing logistics processes, but also aims to draw the attention of more researchers and companies to the ways in which logistics processes are managed and performed in terms of raising energy efficiency. Full article
(This article belongs to the Special Issue Sustainability and Energy Efficiency in Logistics)
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