Rescue path optimization using ant colony systems
| Autor: | Thomas Hanne, Simon Bischof, Manuela Graf, Rolf Dornberger, Marc Poy |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
0209 industrial biotechnology
Mathematical optimization 021103 operations research Computer science Ant colony optimization algorithms 0211 other engineering and technologies 02 engineering and technology Ant colony ComputingMethodologies_ARTIFICIALINTELLIGENCE Drone Vehicle dynamics 020901 industrial engineering & automation Path (graph theory) Vehicle routing problem Motion planning Routing (electronic design automation) |
| Zdroj: | SSCI |
| Popis: | The vehicle routing problem is a well-researched problem with various solutions. Although this problem has been solved many times, there is rarely a case where a solution covers a real-life situation completely. In this paper, a particular dynamic vehicle routing problem is being analyzed. It consists of rescue path planning independently flying drones or driving vehicles in a disaster simulation. The scenario includes continuous updates of injured people that need to be picked up by rescue drones, limited operation range, prioritization of the pickup order depending on the injury level, and a number of people at a certain rescue location. This paper discusses how the dynamic vehicle routing problem can be broken down into a set of static vehicle routing problems. Those problems are then optimized with the help of a particular ant algorithm — in this particular case, an adapted Ant Colony System (ACS). This paper discusses the modelling of the rescue problem as a particular vehicle routing problem and the adaptation of the Ant Colony Optimization (ACO) to solve it. |
| Databáze: | OpenAIRE |
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