Smart City Public Transportation Route Planning Based on Multi-objective Optimization: A Review

Abstract

This paper investigates the implementation of a Multi-Objective Optimization technique for improving public transportation route planning in the setting of smart cities. Recognizing the difficulties of urban mobility, our technique incorporates a variety of criteria, including traffic patterns, cost-effectiveness, and environmental impact, to create an efficient route design system. The research applies complex algorithms to overcome the issues present in existing route planning procedures, using real-world data sources such as GPS data and traffic reports. We illustrate the efficacy of our strategy in boosting time efficiency, lowering costs, and decreasing environmental footprints via extensive case studies. The assessment measures used emphasise the suggested system’s advantages over current techniques. The debate digs into the larger implications for smart city development, recognising limits and providing possibilities for further study. This study adds vital insights and practical answers to the developing subject of smart city transportation, providing a solid basis for the continuing growth of urban mobility.