Optimal search and rescue route design using an improved ant colony optimization

Haichuan Zhang,Baolong Yang,Yinghu Shi,Zhanying Li,Jingwen Sun

doi:10.5755/j01.itc.49.3.25295

Abstract

In this paper, an improved ant colony algorithm is proposed for the route design of maritime emergency search and rescue. To solve the problem that the ant colony algorithm is easy to fall into local optimal solutions in the process of searching, the pheromone concentration updating strategy of the original ant colony algorithm is provided. According to the actual situation of maritime search and rescue, the path weight based on the time of falling into the water is introduced into the algorithm to obtain the optimal route. The simulation results show that the improved algorithm can be used for route design, and obtain the optimal route suitable for sea search and rescue.

Highlights

In recent years, the number and scale of marine activities are increasing, so is the probability of marine accidents
It can effectively alleviate the problem that the Ant Colony Algorithm is prone to fall into the local optimal solution, and the probability of getting an optimal solution increase
The path weight is introduced into the algorithm, so that the obtained optimal path is more in line with the requirements in practical applications

Summary

Introduction

The number and scale of marine activities are increasing, so is the probability of marine accidents. This paper uses an improved ACO to design search and rescue routes. By improving the strategy of pheromone concentration updating in original ACO, the algorithm is more likely to found the optimal solution This alleviates the defect that the Ant Colony Algorithm is easy to fall into the local optimum effectively. According to the actual situation of maritime search and rescue, the path weight based on the time of falling into the water is introduced into the algorithm. This makes the algorithm take the falling time of each target into consideration in the calculation process, so as to make the calculation of the optimal route more reasonable. Combining with the actual situation, the algorithm is introduced with the relevant weight to make the algorithm more meaningful in practical application rescue ships well

Ant Colony Optimization

Algorithm Simulation

The Application of Improved ACO on Search and Rescue Based on Multi-Objective

Findings

Conclusion