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A multi-objective optimization approach to balancing economic efficiency and equity in accessibility to multi-use paths

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  • Chih-Hao Wang

    (California State University, Fresno)

  • Na Chen

    (University of Cincinnati)

Abstract

Improving public health through active transpiration investments has increasingly become a new research focus in transportation planning. This study is to propose a multi-objective optimization modeling framework, through an optimal allocation of active transportation investments, to maximize the total accessibility while minimizing the total differences in accessibility over a city. Accessibility to multi-use paths is calculated for Fresno, California that measures the total length of multi-use paths a resident could reach with a 30-min cycling ride. Then, a geographically weighted regression (GWR) model is used to capture the local relationships between accessibility outcome and previous transportation investments. The marginal-effect analysis for the GWR results indicates economically efficient, inefficient, and indifferent locations for further investments. This study is one of the few to incorporate such a GWR model into a multi-objective optimization modeling framework to improve accessibility to multi-use paths and address inequality issues in transportation. Solving the multi-objective optimization model provides decision-makers a new insight into the making of an economically efficient and socially equal active transportation plan to improve public health.

Suggested Citation

  • Chih-Hao Wang & Na Chen, 2021. "A multi-objective optimization approach to balancing economic efficiency and equity in accessibility to multi-use paths," Transportation, Springer, vol. 48(4), pages 1967-1986, August.
    • Handle: RePEc:kap:transp:v:48:y:2021:i:4:d:10.1007_s11116-020-10117-9
    DOI: 10.1007/s11116-020-10117-9
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    2. Mattoussi, Wided & Mattoussi, Foued & Larnaout, Afrah, 2023. "Optimal subsidization for the adoption of new irrigation technologies," Economic Analysis and Policy, Elsevier, vol. 78(C), pages 1126-1141.

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