Research Article
A Novel Sparrow Particle Swarm Algorithm (SPSA) for Unmanned Aerial Vehicle Path Planning
Algorithm 3
Sparrow particle swarm algorithm (SPSA) pseudocode.
Initialize | Set the basic parameters | Set the start point and target point | Initialize the position of each individual in the population using equations (10)–(12) | Oscillation optimization of all individuals trajectories | For each iteration | Initialize optimal fitness and worst fitness | For each producer | For each dimension | Update the position of by the equation (11) | Set T = 0 | While the position can not reach and T < Tmax | Update the position of by the equation (11) | T = T + 1 | End While | End For | End For | For each scrounger | For each dimension | Update the position of by the equation (4) | Set T = 0 | While the position can not reach and T < Tmax | Update the position of by the equation (4) | T = T + 1 | End While | If T ≥ Tmax | Search for the next position by adaptive escape using equation (12) | End If | End For | End For | For each individual that finds danger | For each dimension | Update the position of by the equation (5) | Set T = 0 | While the position can not reach and T < Tmax | Update the position of by the equation (5) | T = T + 1 | End While | End For | End For | Optimize adaptive oscillation using equation (13) | Update position of all individuals | Calculate and sort fitness values | End For | Perform node optimization on the optimal path and smooth optimization | Return results | Terminate |
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