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Smart city article details
| Title | A New Framework For Multi-Objective Route Planning In Smart Cities |
|---|---|
| ID_Doc | 3033 |
| Authors | Mostafa S.M.; Habashy S.M.; Salem S.A. |
| Year | 2023 |
| Published | Lecture Notes on Data Engineering and Communications Technologies, 152 |
| DOI | http://dx.doi.org/10.1007/978-3-031-20601-6_68 |
| 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. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG. |
| Author Keywords | Ant colony system; Multi-objective grasshopper optimization; Multi-objective optimization route planning; Pareto optimal solution; Travel salesman problem |
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