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Path Optimization Model for Urban Transportation Networks under the Perspective of Environmental Pollution Protection

2021· article· en· 2 citations· W3215960771 on OpenAlex· 10.1155/2021/8952123

Why is this work in the frame?

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Canadian venueIt was published in a Canadian venue.

No Canadian affiliation. An affiliation-only frame — the usual design — would never have seen this work. It is one of the works that make the case for inverting the frame.

Post-publication record

Nature
Retraction
Reason
Concerns/Issues about Data;Concerns/Issues about Results and/or Conclusions;Concerns/Issues about Referencing/Attributions;Concerns/Issues about Peer Review;Investigation by Journal/Publisher;Investigation by Third Party;Paper Mill;Computer-Aided Content or Computer-Generated Content;Unreliable Results and/or Conclusions;
Date
8/9/2023 0:00
Flagged by OpenAlex?
Yes

Source: Retraction Watch, joined by DOI. OpenAlex records retraction as is_retracted, a boolean over a state space with at least four values, so it cannot express an expression of concern, a correction or a reinstatement — it reports them as false, which reads as “fine”.

Abstract

In view of the lack of consideration of environmental protection performance in the traditional path optimization model, a path optimization model for urban traffic networks from the perspective of environmental pollution protection is proposed. Firstly, the urban real-time traffic condition is expressed by the road traffic state index, and an integer programming model is established to optimize the route with the goal of low carbon and shortest distribution time. Then, a hybrid particle swarm optimization algorithm combined with adaptive disturbance mechanism based on variable neighborhood descent is designed, which can better carry out adaptive disturbance according to the situation that the population falls into local extreme value, and the 2-opt local search method is introduced to improve the quality of solution. Finally, the improved particle swarm optimization algorithm is used to solve the two-objective model to obtain the Pareto front solution set, that is, the path scheme under real-time traffic conditions. The experimental demonstration of the proposed model based on two application scenarios shows that its distribution cost, distribution time, and carbon emission are 1975 yuan, 27 h, and 213 kg, respectively, which are better than other comparison models and have high application value.

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The record

Venue
Journal of Advanced Transportation
Topic
Vehicle emissions and performance
Field
Engineering
Canadian institutions
Funders
Keywords
Particle swarm optimizationMathematical optimizationComputer sciencePath (computing)Shortest path problemMulti-objective optimizationPopulationEnvironmental pollutionEnvironmental scienceMathematics
Has abstract in OpenAlex
yes