{"title":"Risk assessment and hybrid algorithm transportation path optimization model for road transport of dangerous goods","authors":"Qiankun Jiang , Haiyan Wang","doi":"10.1016/j.iatssr.2025.01.003","DOIUrl":null,"url":null,"abstract":"<div><div>The current risk assessment methods for dangerous goods roads have the problem of being unable to cope with complex road conditions and the influence of multiple factors. This study extends 9 tertiary indicators from three secondary indicators: personnel factors, vehicle factors, and road factors, to evaluate the transportation risk of dangerous goods. After calculating the weights of each indicator, this study improves the parameters of the particle swarm algorithm using the aggregation and foraging behavior of artificial fish, and uses the improved algorithm to solve the optimal solution for the cost of dangerous goods road transportation. After experimental verification, the improved hybrid algorithm has optimized the path transportation time by 13.9 % compared to a single algorithm model. The total risk of simultaneously improving the algorithm was 0.8863, and the total transportation distance was 861 km, both lower than other algorithms. The comprehensive analysis shows that the established model is reasonable, and the designed improved hybrid algorithm can improve the efficiency of the transportation industry, while also contributing to the improvement of the current cost status of dangerous goods road transportation.</div></div>","PeriodicalId":47059,"journal":{"name":"IATSS Research","volume":"49 1","pages":"Pages 72-80"},"PeriodicalIF":3.2000,"publicationDate":"2025-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IATSS Research","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0386111225000032","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"TRANSPORTATION","Score":null,"Total":0}
引用次数: 0
Abstract
The current risk assessment methods for dangerous goods roads have the problem of being unable to cope with complex road conditions and the influence of multiple factors. This study extends 9 tertiary indicators from three secondary indicators: personnel factors, vehicle factors, and road factors, to evaluate the transportation risk of dangerous goods. After calculating the weights of each indicator, this study improves the parameters of the particle swarm algorithm using the aggregation and foraging behavior of artificial fish, and uses the improved algorithm to solve the optimal solution for the cost of dangerous goods road transportation. After experimental verification, the improved hybrid algorithm has optimized the path transportation time by 13.9 % compared to a single algorithm model. The total risk of simultaneously improving the algorithm was 0.8863, and the total transportation distance was 861 km, both lower than other algorithms. The comprehensive analysis shows that the established model is reasonable, and the designed improved hybrid algorithm can improve the efficiency of the transportation industry, while also contributing to the improvement of the current cost status of dangerous goods road transportation.
期刊介绍:
First published in 1977 as an international journal sponsored by the International Association of Traffic and Safety Sciences, IATSS Research has contributed to the dissemination of interdisciplinary wisdom on ideal mobility, particularly in Asia. IATSS Research is an international refereed journal providing a platform for the exchange of scientific findings on transportation and safety across a wide range of academic fields, with particular emphasis on the links between scientific findings and practice in society and cultural contexts. IATSS Research welcomes submission of original research articles and reviews that satisfy the following conditions: 1.Relevant to transportation and safety, and the multiple impacts of transportation systems on security, human health, and the environment. 2.Contains important policy and practical implications based on scientific evidence in the applicable academic field. In addition to welcoming general submissions, IATSS Research occasionally plans and publishes special feature sections and special issues composed of invited articles addressing specific topics.