UAV route planning using Multiobjective Ant Colony System

Author(s):  
Wang Zhenhua ◽  
Zhang Weiguo ◽  
Shi Jingping ◽  
Han Ying
Author(s):  
Yipeng Zhou ◽  
Junping Du ◽  
Feng Xu ◽  
Yang Yang ◽  
Xuyan Tu

2018 ◽  
pp. 5-12

Optimización de rutas de vehículos con enfoque multiobjetivo mediante Sistema Basado en Colonia de Hormigas en una Empresa de transporte de Personal John P. Portella Melchor, Carool E. Tomasto Farfan, Hugo F. Vega Huerta, Zoraida Mamani Rodríguez Facultad de Ingeniería de Sistemas e Informática, Universidad Nacional Mayor de San Marcos, Lima, Perú Recibido el 15 de junio del 2017. Revisado el 21 de junio del 2017. Aceptado el 1 de julio del 2017 DOI: https://doi.org/10.33017/RevECIPeru2017.0001/ Resumen El presente proyecto tiene como objetivo mejorar la planificación de rutas mediante la disminución de la distancia total recorrida de viaje y la cantidad de vehículos a emplear en una empresa de transporte, la cual se dedica al traslado privado de personal de sus clientes corporativos. El proceso de planificación de rutas de este tipo de empresas es completamente manual y su factor de éxito es la experiencia del planificador y el conocimiento de los conductores que realizan los recorridos diarios sobre las calles de Lima Metropolitana, siendo estas las principales causas de que se origen los problemas de uso excesivo de vehículos y largas distancias en el recorrido. En ese contexto, la propuesta de solución inicia analizando los procesos de planificación de la empresa, para luego proceder a buscar alternativas de solución expresados en algoritmos que puedan realizar de manera óptima el cálculo de las rutas. Se escoge el Sistema Basado en Colonia de Hormigas, luego se elabora el modelo matemático, se adapta el algoritmo a las condiciones del negocio para luego realizar la implementación, y así finalmente realizar pruebas y calibrar los parámetros del algoritmo con el fin de obtener valores que mejoren los resultados obtenidos. Los beneficios que se obtienen para la empresa son la reducción de vehículos y distancias más cortas, lo que concluye en reducción de costos y mejora de la calidad del servicio. Descriptores: Planificación, Optimización, Rutas, Sistema Basado en Colonia de Hormigas, Algoritmo. Abstract This project is aimed at improving route planning by decreasing the total travel distance and the number of vehicles used by a provate transportation company dedicated to driving its corporate clients' staff. This type of companies carries out their route planning process manually and their success is highly dependent on the planner's experience and the know-how of drivers who go along the streets of Lima Metropolitana on a daily basis. These are the main reasons behind the problems related to excessive use of vehicles and the long travel distances to cover. In this context, the proposed solution starts by analyzing the company's planning processes, and then proceed to search for alternative solutions expressed in algorithms that can optimally perform the calculation of the routes. A system based on an ant colony is chosen, then a mathematical model is prepared, and the algorithm is adapted to the conditions of this business. Finally, we implements and test it, adjusting the algorithm's parameters in order to get values that improve the obtained results. The benefits for the company are the reduction in the number of vehicles and the shortening of distances, which in turn results in cost reduction and service quality improvement. Keywords: Planning, Optimization, Route, Ant Colony System, Algorithms.


2021 ◽  
Vol 9 (2) ◽  
pp. 220
Author(s):  
Linfan Liu ◽  
Huajun Zhang ◽  
Jupeng Xie ◽  
Qin Zhao

The emergency evacuation route planning of cruise ships directly affects the safety of all crew members and passengers during emergencies. Research on the planning of emergency evacuation routes for cruise ships is a frontier subject of maritime safety. This study proposes an improved ant colony system (IACS) to solve the evacuation route planning of crowds on cruise ships. The IACS, which is different from common single-path ant colony system (ACS) evacuation algorithms, is used to solve the multipath planning problem of crowd evacuation from cruise ships by considering crowd density and speed in the model. An increasing flow method is introduced into the IACS to improve the efficiency of the proposed algorithm. Numerical experiments show that this method meets the requirements of evacuation analysis guidelines for new and existing passenger ships (MSC.1/Circ.1533)and can effectively and efficiently plan the emergency evacuation path for cruise ship crowd.


2021 ◽  
Vol 18 (3) ◽  
pp. 172988142110192
Author(s):  
Songcan Zhang ◽  
Jiexin Pu ◽  
Yanna Si ◽  
Lifan Sun

Path planning of mobile robots in complex environments is the most challenging research. A hybrid approach combining the enhanced ant colony system with the local optimization algorithm based on path geometric features, called EACSPGO, has been presented in this study for mobile robot path planning. Firstly, the simplified model of pheromone diffusion, the pheromone initialization strategy of unequal allocation, and the adaptive pheromone update mechanism have been simultaneously introduced to enhance the classical ant colony algorithm, thus providing a significant improvement in the computation efficiency and the quality of the solutions. A local optimization method based on path geometric features has been designed to further optimize the initial path and achieve a good convergence rate. Finally, the performance and advantages of the proposed approach have been verified by a series of tests in the mobile robot path planning. The simulation results demonstrate that the presented EACSPGO approach provides better solutions, adaptability, stability, and faster convergence rate compared to the other tested optimization algorithms.


IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Tanzila Saba ◽  
Amjad Rehman ◽  
Rabia Latif ◽  
Suliman Mohamed Fati ◽  
Mudassar Raza ◽  
...  

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