A New Framework for Multi-objective Route Planning in Smart Cities

Proceedings of the 8th International Conference on Advanced Intelligent Systems and Informatics 2022(2022)

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Abstract
Route planning is a crucial map navigation feature. Nevertheless, standard commercial map programs only offer optimum routes based on a particular objective, such as time, distance, or other metrics, and disregard the safety objective. Therefore, there is a need for a multi-objective criterion to avoid accidents and to be able to locate not only a short route but also a safe route. This paper proposes a new framework for multi-objective route planning in smart cities. The framework is evaluated by multiple symmetric travelling salesman problem (TSP) instances with varying scale sizes. Several assessment measures are employed to evaluate the proposed framework. The experimental findings demonstrate that the proposed multi-objective framework outperforms and achieves the safety goals compared with other alternatives that considered only the shortest path objective. These findings reveal the robustness of the proposed framework that could be used as a reliable tool for improving the safety and management of road traffic.
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Key words
Multi-objective optimization route planning,Ant colony system,Travel salesman problem,Multi-objective grasshopper optimization,Pareto optimal solution
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