Abstract: Aiming at the path optimization problem that needs to be solved frequently in GIS spatial analysis, this paper studies a new type of swarm intelligent space path optimization algorithm, called seagull optimization algorithm (SOA). By redefining the representation and update strategy of seagull position, the seagull optimization algorithm is converted from continuous domain to discrete domain, and then the discrete seagull optimization algorithm is established(DSOA). At the same time, in order to make the seagull to jump out of the local optimal value, a random variable factor is introduced. In order to verify the reliability of DSOA, by defining the fitness function and feasible solution space, the discrete seagull optimization algorithm is used to solve the traveling salesman problem(TSP). The results experimental results show that DSOA has good robustness in solving optimal path problems and has strong application potential in spatial analysis.

Key words: swarm intelligence, optimization algorithm, seagull, discrete, path optimization