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Sustainability
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Optimization in Sustainable Design and Location of Networked Facilities and...
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Optimization in Sustainable Design and Location of Networked Facilities and Reverse Logistics

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

Deadline for manuscript submissions: closed (31 March 2023) | Viewed by 1815

Special Issue Editors

Prof. Dr. Ali Elkamel

E-Mail Website
Guest Editor
Department of Chemical Engineering, University of Waterloo, 200 University Avenue West, Waterloo, ON N2L 3G1, Canada
Interests: energy and environmental engineering systems; air pollution modeling, simulation anenergy and environmental engineering systems; air pollution modeling; planning and optimization; sustainable development of the petrochemical industry
Special Issues, Collections and Topics in MDPI journals
Dr. Ali Ahmadian

E-Mail Website
Guest Editor
Department of Chemical Engineering, University of Waterloo, Canada and Department of Electrical Engineering, University of Bonab, Bonab P.O. Box 5551761167, Iran
Interests: energy economics; energy and environment; transportation electrification; smart energy hubs; machine learning
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The quest for sustainable development requires integrating environmental, economic, and social welfare. Optimal sustainable design and the location of networked facilities and reverse logistics represent important pillars to achieve such integration. Different important factors, such as minimizing the performance costs and environmental pollution and increasing sustainability and reliability should be considered in decision making models. Moreover, critical uncertainties characteristic to the reverse logistics operations should be taken into account in sustainability studies. Furthermore, the risk associated with these uncertain parameters should be managed to reduce the related risk in the uncertain environment, and the flexibility of designed systems should be increased under different conditions. This Special Issue provides an opportunity for researchers to present new optimization models in the sustainable design and location of networked facilities and reverse logistics, to decrease performance cost and environmental pollution and increase sustainability and reliability.

Topics of interest include, but are not limited to:

  • Optimization models for sustainable reverse logistics network design
  • Reverse logistics network design for end-of -life vehicles
  • Network optimization models in waste reverse supply chains
  • Network optimization models in energy supply chains
  • Reverse logistics network design for sustainable treatment of multi-sourced waste
  • Sustainable supply chain network design
  • Sustainable community design
  • Multi-period planning horizon for sustainable development
  • Optimal location of new industries in existing industrial areas
  • Combined facility location and network design
  • Optimization in decentralized production systems

Prof. Dr. Ali Elkamel
Dr. Ali Ahmadian
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

  • optimization in sustainable design
  • location of networked facilities
  • reverse logistics
  • urban underground logistics network
  • multi-objective optimization
  • cost and pollution minimization
  • increasing the sustainability and reliability
  • uncertainty and risk management
  • environmental regulations

Published Papers (1 paper)

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Research

16 pages, 3545 KiB  
Article
Non-Intrusive Load Monitoring of Residential Loads via Laplacian Eigenmaps and Hybrid Deep Learning Procedures
by Arash Moradzadeh, Sahar Zakeri, Waleed A. Oraibi, Behnam Mohammadi-Ivatloo, Zulkurnain Abdul-Malek and Reza Ghorbani
Sustainability 2022, 14(22), 14898; https://doi.org/10.3390/su142214898 - 11 Nov 2022
Cited by 7 | Viewed by 1174
Abstract
Today, introducing useful and practical solutions to residential load disaggregation as subsets of energy management has created numerous challenges. In this study, an intelligence hybrid solution based on manifold learning and deep learning applications is presented. The proposed solution presents a combined structure [...] Read more.
Today, introducing useful and practical solutions to residential load disaggregation as subsets of energy management has created numerous challenges. In this study, an intelligence hybrid solution based on manifold learning and deep learning applications is presented. The proposed solution presents a combined structure of Laplacian eigenmaps (LE), a convolutional neural network (CNN), and a recurrent neural network (RNN), called LE-CRNN. In the proposed model architecture, LE, with its high ability in dimensional reduction, transfers the salient features and specific values of power consumption curves (PCCs) of household electrical appliances (HEAs) to a low-dimensional space. Then, the combined model of CRNN significantly improves the structure of CNN in fully connected layers so that the process of identification and separation of the HEA type can be performed without overfitting problems and with very high accuracy. In order to implement the suggested model, two real-world databases have been used. In a separate scenario, a conventional CNN is applied to the data for comparing the performance of the suggested model with the CNN. The designed networks are trained and validated using the PCCs of HEAs. Then, the whole energy consumption of the building obtained from the smart meter is used for load disaggregation. The trained networks, which contain features extracted from PCCs of HEAs, prove that they can disaggregate the total power consumption for houses intended for the Reference Energy Disaggregation Data Set (REDD) and Almanac of Minutely Power Dataset (AMPds) with average accuracies (Acc) of 97.59% and 97.03%, respectively. Finally, in order to show the accuracy of the developed hybrid model, the obtained results in this study are compared with the results of similar works for the same datasets. Full article
(This article belongs to the Special Issue Optimization in Sustainable Design and Location of Networked Facilities and Reverse Logistics)
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