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Optimization of Sustainable Transport and Logistics Processes

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainable Transportation".

Deadline for manuscript submissions: closed (13 April 2024) | Viewed by 2867

Special Issue Editors


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Guest Editor
Institut FEMTO-ST, UTBM, CNRS, CEDEX, F-90010 Belfort, France
Interests: operational research; optimization; planning and scheduling and their application to industrial and logistic systems (manufacturing and services); shop scheduling problems with transportation resources; vehicle routing problems, public transportation planning; sustainable supply chains and transport scheduling in ports

E-Mail Website
Guest Editor
Institut FEMTO-ST, UTBM, CNRS, CEDEX, F-90010 Belfort, France
Interests: operational research; optimization; linear programming; planning and scheduling and their application to industrial and logistic systems (manufacturing and services); shop scheduling problems with transportation resources; vehicle routing problems and sustainable supply chains

Special Issue Information

Dear Colleagues,

We invite authors to submit their original papers to this Special Issue, which aims to establish an overview of research activity on the “Optimization of Sustainable Transport and Logistics Processes” in an industrial and social context dominated by both digitalization—which has advantages and drawbacks for humans and the environment (such as higher energy consumption)—and environmental transition, which involves tougher legislative constraints on fossil fuels and incentives to use renewable energies, and to sort and recycle used products and packaging. These contexts have enriched and complicated many classical scientific optimization problems that are widely addressed in logistics and transport. These problems range from the strategic level, such as the design and optimization of supply chains (including reverse logistics), to tactical and operational levels, such as routing problems including, for example, the use of electric vehicles. The sustainable optimization of logistics and transport systems and activities aims to reduce their costs while limiting their environmental impact (for example, the depletion of natural resources, CO2 emissions and energy consumption peaks) and considering social aspects (for example, avoiding the degradation of employability and working conditions for humans). 

In this Special Issue, original research articles and reviews are welcome. We are interested in recent research advances in improving the sustainability of transport and logistics activities, ranging from the supply of raw materials to the transformation processes, storage, packaging, distribution and management of products at the end of their lifecycle. Contributions may include (but are not limited to):

- The formalization of new trends and challenges in logistics and transport, involving one or several sustainability dimensions.

- The definition of new optimization indicators, criteria and metrics for sustainability assessment and optimization.

- Modeling, optimisation methods (operations research, simulation and artificial intelligence), decision support methods in a multi-objective context, or sustainability practices (collaboration, mutualization, intermodality/multimodality, etc.).

Prof. Dr. Marie-Ange Manier
Dr. Hervé Manier
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. Sustainability 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 2400 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

  • sustainability
  • optimization
  • supply chain
  • logistics
  • transport
  • sustainability indicators
  • model
  • optimization methods and algorithms
  • multi-objective decision support

Published Papers (2 papers)

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Research

29 pages, 8221 KiB  
Article
A Drone Scheduling Method for Emergency Power Material Transportation Based on Deep Reinforcement Learning Optimized PSO Algorithm
by Wenjiao Zai, Junjie Wang and Guohui Li
Sustainability 2023, 15(17), 13127; https://doi.org/10.3390/su151713127 - 31 Aug 2023
Cited by 1 | Viewed by 910
Abstract
Stable material transportation is essential for quickly restoring the power system following a disaster. Drone-based material transportation can bypass ground transportation’s limitations and reduce transit times. However, the current drone flight trajectory distribution optimization model cannot meet the need for mountainous emergency relief [...] Read more.
Stable material transportation is essential for quickly restoring the power system following a disaster. Drone-based material transportation can bypass ground transportation’s limitations and reduce transit times. However, the current drone flight trajectory distribution optimization model cannot meet the need for mountainous emergency relief material distribution following a disaster. A power emergency material distribution model with priority conditions is proposed in this paper, along with a two-layer dynamic task-solving framework that takes task dynamics into account. This research proposes an algorithm (TD3PSO) that combines the particle swarm algorithm (PSO) updating technique with the double-delay depth deterministic policy gradient algorithm (TD3) algorithm’s capacity to dynamically parameterize. The final task allocation experiment demonstrates that the modified TD3PSO significantly outperforms the conventional algorithm on the Solomon data set, with an improvement of 26.3% on average over the RLPSO algorithm and a 11.0% reduction in the volatility of the solving impact. When solving under realistic circumstances, the solution effect increases by 1.6% to 13.4%, and the redistribution experiment confirms the framework’s efficacy. As a result, the algorithm and architecture suggested in this paper may successfully address the issue of scheduling drones for power emergencies while enhancing transportation efficiency. Full article
(This article belongs to the Special Issue Optimization of Sustainable Transport and Logistics Processes)
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22 pages, 2588 KiB  
Article
Multi-Objective Optimization of the Multimodal Routing Problem Using the Adaptive ε-Constraint Method and Modified TOPSIS with the D-CRITIC Method
by Apichit Maneengam
Sustainability 2023, 15(15), 12066; https://doi.org/10.3390/su151512066 - 07 Aug 2023
Cited by 1 | Viewed by 1124
Abstract
This paper proposes a multi-criteria decision-making approach for the multimodal routing problem (MRP) of bulk transportation in Thailand to minimize the total cost, transportation time, and total carbon dioxide-equivalent (CO2e) emissions simultaneously. The proposed approach has three phases: The first phase [...] Read more.
This paper proposes a multi-criteria decision-making approach for the multimodal routing problem (MRP) of bulk transportation in Thailand to minimize the total cost, transportation time, and total carbon dioxide-equivalent (CO2e) emissions simultaneously. The proposed approach has three phases: The first phase is generating all nondominated solutions using Kirlik and Sayin’s adaptive ε-constraint method. In the second phase, the Distance Correlation-based Criteria Importance Through Inter-criteria Correlation (D-CRITIC) method is used to determine the weight of each objective function and assign it to the modified technique for order of preference by similarity to ideal solution (modified TOPSIS) model in next phase. The third phase consists of ranking Pareto solutions obtained from the first phase using the modified TOPSIS. This proposed approach is applied to a real-world problem to enable the selection of the best route for transporting goods from the anchorage area in the Gulf of Thailand to the destination factory throughout a multimodal transportation network in Thailand. The computational results indicate that the proposed approach is superior to the current approach utilizing the ε-constraint method (ECM) regarding the number of Pareto solutions obtained and the proportion of computational time to the number of Pareto solutions obtained. Finally, the proposed method can solve the MRP with three or more objective functions and provide a multimodal route selection approach that is suitable for decision makers to offer a multimodal route to customers in the negotiation process for outsourcing transportation. Full article
(This article belongs to the Special Issue Optimization of Sustainable Transport and Logistics Processes)
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