Research on Multi-objective Shortest Path Based on Genetic Algorithm

The shortest path problem is a search for the shortest or minimum path between the source and destination under the relevant parameter constraints, and it is an effective method for solving network routing problems. Many good algorithms have been proposed by researchers for single-parameter shortest...

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Vydáno v:2022 2nd International Conference on Computer Science and Blockchain (CCSB) s. 127 - 130
Hlavní autoři: Zheng, Sihai, Zheng, Changrui, Li, Wei
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: IEEE 01.10.2022
Témata:
Adaptation value
Biological system modeling
Encoding
Genetic algorithm
MNET
Path growth
Quality of service
Routing
Routing protocols
Search problems
Shortest path
Shortest path problem
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Shrnutí:The shortest path problem is a search for the shortest or minimum path between the source and destination under the relevant parameter constraints, and it is an effective method for solving network routing problems. Many good algorithms have been proposed by researchers for single-parameter shortest path problems, but the process of finding shortest paths for multiple parameters is an NP-complete problem, and less research has been done. In this paper, a multi-objective shortest path algorithm MQGASP based on genetic algorithm is proposed, which regards the feasible solution of the nearest ideal solution of partial distance measurement as the solution to be found. Because the priority based coding method can potentially represent all possible paths in the directed graph, it can well represent the paths in the network graph with chromosomes. Simulation experiments show that the MQGASP algorithm has better performance in solving multi-QoS routing and is able to find the shortest transmission path with maximum bandwidth and minimum delay.
DOI:10.1109/CCSB58128.2022.00030