{"title":"Optimization of transport sustainability index to conserve resources: A case study of Delhi, India","authors":"","doi":"10.1016/j.cstp.2024.101316","DOIUrl":null,"url":null,"abstract":"<div><div>The objective of the study is to propose a methodology for optimization of Transport Sustainability Index (TSI) of National Capital Territory (NCT) of Delhi since maximum value of TSI i.e. 1.0 will occur when all the sustainability indicators attain their extremum values simultaneously, which is highly improbable. TSI is estimated using 29 most appropriate transport sustainability indicators under four pillars of sustainability, viz. environmental, social, economic, and technological. Optimization of TSI involves following steps, viz. identification of three independent variables, i.e. fuel consumption (X<sub>1</sub>), registered vehicles (X<sub>2</sub>) and population (X<sub>3</sub>) which influence all the indicators, data collection in respect of indicators and influencing variables for 30-year time period (from year 2000 to 2030), evolution of regression equations between indicators and influencing variables, and formulation of TSI as a multi-variate non-linear expression in terms of influencing variables, which is used for optimization. The generalized reduced gradient non-linear programming optimization technique is used to solve for the optimum values of influencing variables (X<sub>1</sub><sup>opt</sup>, X<sub>2</sub><sup>opt</sup>, X<sub>3</sub><sup>opt</sup>) as 0.0988, 0.4709 & 0.0 respectively and optimum value of TSI (TSI<sup>opt</sup>) as 0.71, which is 25% higher than the TSI of 0.59 for the year 2023–24. The knowledge of optimum value of TSI would help the city transport policy planners to allocate, only that much quantum of infrastructural and financial resources so as to reach optimum rather than extremum values, which leads to potential savings or conservation of resources. An overall notional savings of 58% has been estimated by the study.</div></div>","PeriodicalId":46989,"journal":{"name":"Case Studies on Transport Policy","volume":null,"pages":null},"PeriodicalIF":2.4000,"publicationDate":"2024-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Case Studies on Transport Policy","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2213624X24001718","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 objective of the study is to propose a methodology for optimization of Transport Sustainability Index (TSI) of National Capital Territory (NCT) of Delhi since maximum value of TSI i.e. 1.0 will occur when all the sustainability indicators attain their extremum values simultaneously, which is highly improbable. TSI is estimated using 29 most appropriate transport sustainability indicators under four pillars of sustainability, viz. environmental, social, economic, and technological. Optimization of TSI involves following steps, viz. identification of three independent variables, i.e. fuel consumption (X1), registered vehicles (X2) and population (X3) which influence all the indicators, data collection in respect of indicators and influencing variables for 30-year time period (from year 2000 to 2030), evolution of regression equations between indicators and influencing variables, and formulation of TSI as a multi-variate non-linear expression in terms of influencing variables, which is used for optimization. The generalized reduced gradient non-linear programming optimization technique is used to solve for the optimum values of influencing variables (X1opt, X2opt, X3opt) as 0.0988, 0.4709 & 0.0 respectively and optimum value of TSI (TSIopt) as 0.71, which is 25% higher than the TSI of 0.59 for the year 2023–24. The knowledge of optimum value of TSI would help the city transport policy planners to allocate, only that much quantum of infrastructural and financial resources so as to reach optimum rather than extremum values, which leads to potential savings or conservation of resources. An overall notional savings of 58% has been estimated by the study.