Improved Genetic Algorithm-based Network Game Path Selection and Simulation

Authors

Jianping Gu, 1. Lishui University, Lishui 323000, China;;
Mingmin Zhang, 2. Zhejiang University, Hangzhou 310000, China;
Meiliang Wang, 1. Lishui University, Lishui 323000, China;;

Abstract

Abstract: Traditional optimal path algorithm only sets the shortest path as the target, and it does not consider the network congestion and the number of users in game area for real-time situation, thus resulting in some limitations. According to the actual circumstance of network game, network game path selection model was proposed, and the improved genetic algorithm was employed for simulation. The method pre-processed the game map to get each road weighted length value for a real-time game map, and optimization solution was obtained through the genetic algorithm. A network game path selection method based on improved genetic algorithm was proposed compared with the classical dijkstra algorithm, effectively improving the efficiency of the path search.

Recommended Citation

Gu, Jianping; Zhang, Mingmin; and Wang, Meiliang (2020) "Improved Genetic Algorithm-based Network Game Path Selection and Simulation," Journal of System Simulation: Vol. 28: Iss. 8, Article 14.
Available at: https://dc-china-simulation.researchcommons.org/journal/vol28/iss8/14

First Page

1805

Revised Date

2015-02-01

DOI Link

https://doi.org/

Last Page

1811

CLC

TP391.9

Recommended Citation

Gu Jianping, Zhang Mingmin, Wang Meiliang. Improved Genetic Algorithm-based Network Game Path Selection and Simulation[J]. Journal of System Simulation, 2016, 28(8): 1805-1811.