Bedoukian   RussellIPM   RussellIPM   Piezoelectric Micro-Sprayer


Home
Animal Taxa
Plant Taxa
Semiochemicals
Floral Compounds
Semiochemical Detail
Semiochemicals & Taxa
Synthesis
Control
Invasive spp.
References

Abstract

Guide

Alphascents
Pherobio
InsectScience
E-Econex
Counterpart-Semiochemicals
Print
Email to a Friend
Kindly Donate for The Pherobase

« Previous AbstractFlavor characteristics of peeled walnut kernels under two-steps roasting processes    Next AbstractDetection of Lung Cancer: Concomitant Volatile Organic Compounds and Metabolomic Profiling of Six Cancer Cell Lines of Different Histological Origins »

IEEE Trans Cybern


Title:A Bilevel Ant Colony Optimization Algorithm for Capacitated Electric Vehicle Routing Problem
Author(s):Jia YH; Mei Y; Zhang M;
Address:
Journal Title:IEEE Trans Cybern
Year:2022
Volume:20220919
Issue:10
Page Number:10855 - 10868
DOI: 10.1109/TCYB.2021.3069942
ISSN/ISBN:2168-2275 (Electronic) 2168-2267 (Linking)
Abstract:"The development of electric vehicle (EV) techniques has led to a new vehicle routing problem (VRP) called the capacitated EV routing problem (CEVRP). Because of the limited number of charging stations and the limited cruising range of EVs, not only the service order of customers but also the recharging schedules of EVs should be considered. However, solving these two aspects of the problem together is very difficult. To address the above issue, we treat CEVRP as a bilevel optimization problem and propose a novel bilevel ant colony optimization algorithm in this article, which divides CEVRP into two levels of subproblem: 1) capacitated VRP and 2) fixed route vehicle charging problem. For the upper level subproblem, the electricity constraint is ignored and an order-first split-second max-min ant system algorithm is designed to generate routes that fulfill the demands of customers. For the lower level subproblem, a new effective heuristic is designed to decide the charging schedule in the generated routes to satisfy the electricity constraint. The objective values of the resultant solutions are used to update the pheromone information for the ant system algorithm in the upper level. Through good orchestration of the two components, the proposed algorithm can significantly outperform state-of-the-art algorithms on a wide range of benchmark instances"
Keywords:
Notes:"PubMed-not-MEDLINEJia, Ya-Hui Mei, Yi Zhang, Mengjie eng 2021/04/21 IEEE Trans Cybern. 2022 Oct; 52(10):10855-10868. doi: 10.1109/TCYB.2021.3069942. Epub 2022 Sep 19"

 
Back to top
 
Citation: El-Sayed AM 2024. The Pherobase: Database of Pheromones and Semiochemicals. <http://www.pherobase.com>.
© 2003-2024 The Pherobase - Extensive Database of Pheromones and Semiochemicals. Ashraf M. El-Sayed.
Page created on 27-12-2024