Asset Details
Do you wish to reserve the book?
Based on Improved NSGA-II Algorithm for Solving Time-Dependent Green Vehicle Routing Problem of Urban Waste Removal with the Consideration of Traffic Congestion: A Case Study in China
Hey, we have placed the reservation for you!
By the way, why not check out events that you can attend while you pick your title.
Oops! Something went wrong.
Looks like we were not able to place the reservation. Kindly try again later.
Are you sure you want to remove the book from the shelf?
Based on Improved NSGA-II Algorithm for Solving Time-Dependent Green Vehicle Routing Problem of Urban Waste Removal with the Consideration of Traffic Congestion: A Case Study in China
Do you wish to request the book?
Based on Improved NSGA-II Algorithm for Solving Time-Dependent Green Vehicle Routing Problem of Urban Waste Removal with the Consideration of Traffic Congestion: A Case Study in China
Please be aware that the book you have requested cannot be checked out. If you would like to checkout this book, you can reserve another copy
We have requested the book for you!
Your request is successful and it will be processed during the Library working hours. Please check the status of your request in My Requests.
Oops! Something went wrong.
Looks like we were not able to place your request. Kindly try again later.
Journal Article
Based on Improved NSGA-II Algorithm for Solving Time-Dependent Green Vehicle Routing Problem of Urban Waste Removal with the Consideration of Traffic Congestion: A Case Study in China
2023
Overview
The dense population and the large amount of domestic waste generated make it difficult to determine the best route and departure time for waste removal trucks in a city. Aiming at the problems of municipal solid waste (MSW) removal and transportation not in time, high collection and transportation costs and high carbon emissions, this paper studies the vehicle routing problem of municipal solid waste removal under the influence of time-dependent travel time, traffic congestion and carbon emissions. In this paper, a dual objective model with the lowest total economic cost and the highest garbage removal efficiency is established, and a DCD-DE-NSGAII algorithm based on Dynamic Crowding Distance and Differential Evolution is designed to improve the search ability, improve the convergence speed and increase the diversity of the optimal solution set. The results show that: according to the actual situation of garbage collection and transportation, the method can scientifically plan the garbage collection and transportation route, give a reasonable garbage collection scheme and departure time, and effectively avoid traffic congestion time; Through algorithm comparison, the algorithm and model proposed in this paper can reduce collection and transportation costs, improve transportation efficiency and reduce environmental pollution.
Publisher
MDPI AG
Subject
