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Sustainability
Special Issues
Optimization in Logistics and Mobility Using Metaheuristics
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Optimization in Logistics and Mobility Using Metaheuristics

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

Deadline for manuscript submissions: closed (29 February 2020) | Viewed by 6535

Special Issue Editors

Prof. Dr. Kenneth Sörensen

E-Mail Website
Guest Editor
Department of Engineering Management, University of Antwerp, 2000 Antwerp, Belgium
Interests: logistical planning; optimization; (meta) heuristics; vehicle routing; humanitarian logistics; horizontal collaboration; public transport planning
Prof. Dr. Marc Sevaux

E-Mail Website
Guest Editor
Lab-STICC, University of South Brittany, F56321 Lorient, France
Interests: design of heuristics and metaheuristics; mathematical programming; matheuristics; routing problems; optimization in electronic design; wireless sensor networks; scheduling
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

We invite submissions to a Special Issue of Sustainability on “Optimization in Logistics and Mobility Using Metaheuristics”. This Special Issue will focus on innovative methods to solve realistic or real-life optimization problems arising in the transportation of either goods (logistics) or people (mobility).

Contributions that focus on the sustainability aspects of optimization in logistics and mobility are especially welcomed (e.g., minimizing the ecological footprint). We encourage the submission of papers that discuss real-life optimization problems and acknowledge that it might be difficult to perform a strictly computational comparison of the algorithms developed to solve these problems.

Prof. Dr. Kenneth Sörensen
Prof. Dr. Marc Sevaux
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
  • Logistics
  • Mobility
  • Heuristics
  • Metaheuristics

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Published Papers (1 paper)

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Research

23 pages, 5338 KiB  
Article
Intelligent Intersection Control for Delay Optimization: Using Meta-Heuristic Search Algorithms
by Arshad Jamal, Muhammad Tauhidur Rahman, Hassan M. Al-Ahmadi, Irfan Ullah and Muhammad Zahid
Sustainability 2020, 12(5), 1896; https://doi.org/10.3390/su12051896 - 2 Mar 2020
Cited by 54 | Viewed by 5994
Abstract
Traffic signal control is an integral component of an intelligent transportation system (ITS) that play a vital role in alleviating traffic congestion. Poor traffic management and inefficient operations at signalized intersections cause numerous problems as excessive vehicle delays, increased fuel consumption, and vehicular [...] Read more.
Traffic signal control is an integral component of an intelligent transportation system (ITS) that play a vital role in alleviating traffic congestion. Poor traffic management and inefficient operations at signalized intersections cause numerous problems as excessive vehicle delays, increased fuel consumption, and vehicular emissions. Operational performance at signalized intersections could be significantly enhanced by optimizing phasing and signal timing plans using intelligent traffic control methods. Previous studies in this regard have mostly focused on lane-based homogenous traffic conditions. However, traffic patterns are usually non-linear and highly stochastic, particularly during rush hours, which limits the adoption of such methods. Hence, this study aims to develop metaheuristic-based methods for intelligent traffic control at isolated signalized intersections, in the city of Dhahran, Saudi Arabia. Genetic algorithm (GA) and differential evolution (DE) were employed to enhance the intersection’s level of service (LOS) by optimizing the signal timings plan. Average vehicle delay through the intersection was selected as the primary performance index and algorithms objective function. The study results indicated that both GA and DE produced a systematic signal timings plan and significantly reduced travel time delay ranging from 15 to 35% compared to existing conditions. Although DE converged much faster to the objective function, GA outperforms DE in terms of solution quality i.e., minimum vehicle delay. To validate the performance of proposed methods, cycle length-delay curves from GA and DE were compared with optimization outputs from TRANSYT 7F, a state-of-the-art traffic signal simulation, and optimization tool. Validation results demonstrated the adequacy and robustness of proposed methods. Full article
(This article belongs to the Special Issue Optimization in Logistics and Mobility Using Metaheuristics)
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