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

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.