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Table 1 Symbol and descriptions in this paper

From: Task allocation and route planning of multiple UAVs in a marine environment based on an improved particle swarm optimization algorithm

Symbol

Description

U

The set of UAVs

O

The set of offshore platforms

C

The set of tasks. \(c_0\) is the warehouse center

\(H_i\)

The set of wireless links

\(g_p\)

The iterations of particles

\(\rho _i\)

The density of UAVs within the coverage of offshore platforms \(o_i\)

\(Q_k(x_i,y_i)\)

The coordinates of UAV \(u_k\)

\(\varphi _{k,i}\)

The Signal noise ratio (SNR) of UAV under offshore platform \(o_i\)

\(p_k\)

The transmission power of UAV \(u_k\)

\(\mu _k,_i\)

The route loss index from UAV \(u_k\) to offshore platform \(o_i\)

\(\sigma\)

The additive white Gaussian noise

\(N_u,N_c\)

The number of UAVs and task points

D

The total path of the UAV

\(q_i\)

The material demand of the task point \(c_i\)

\(t_k,v_k\)

The travel time and speed of UAV \(u_k\)

\(d_{i,j}\)

The distance between task point \(c_i\) and task point \(c_j\)

\(d_k\)

The distance that UAV has traveled

\(l_{kmax},l_{kmin}\)

The maximum range and minimum inertial distance of UAV \(u_k\)

\(l_{ki},L_k\)

Segment i and the total travel of UAV \(u_k\)

\(\theta _{kmax}\)

The maximum horizontal deflection angle of UAV \(u_k\)

F

The fitness function of route planning

\(G_0\)

The threat zone collision factor

\(N_p\)

The number of particles

P

The set of particles

\(Pbest_i,Gbest_i\)

The local optimal solution and global optimal solution of particle

\(a_1,a_2,c_1,c_2,\omega\)

The acceleration constants, random function, and inertia variable of particles, respectively