Randomized greedy parameters.

Improving non-motorized accessibility is essential to enable access to vital services such as education and healthcare. Road networks are often inadequately designed for non-motorized accessibility, and service facilities are not always strategically located to reach the majority of users. Furthermore, design decisions are rarely made with consideration for the diverse needs and walking abilities of a heterogeneous population. Enhancing infrastructure by locating new service facilities and creating accessible paths involves significant investments, requiring a systematic approach to utilize limited resources efficiently. We propose an optimization model to identify optimal locations for new facilities and accessible road segments to maximize non-motorized accessibility to a range of services, taking into account users with different walking abilities. A randomized greedy algorithm is developed to tackle the complex network design and facility location problem. A case study in the Huai Kwang district of Bangkok is discussed to illustrate how this methodology can support strategic decisions to enhance non-motorized accessibility.