Nature-inspired metaheuristic optimization algorithms for urban transit routing problem

Abstract

Designing urban transportation networks is a technological and social reality defined as a decentralized polynomial NP-Hard problem. In order to efficiently resolve this issue, several nature-inspired metaheuristic approaches have been proposed. Although these methods are crucial to resolving urban transportation network challenges, no comprehensive study has been conducted to address these concerns. Thus, this study provides an in-depth examination of nature-inspired metaheuristic methods applied to urban transmission. The current study aims to demonstrate the significant benefits of optimization algorithms in solving the Urban Transit Routing Problem (UTRP).