Improved artificial fish school optimization method based on vehicle path planning
An artificial fish school and vehicle path technology, applied in the engineering field, can solve the problems of low precision of optimization results, slow operation speed, and poor ability of the algorithm to maintain a balance between exploration and development, and achieve the effect of improving the global search ability.
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[0029] An improved artificial fish swarm optimization method based on vehicle path planning, specifically comprising the following steps:
[0030] Step 1. Considering the characteristics of the VRPB problem, randomly generate artificial fish schools of initial size. The state of the vehicle in period t is defined by the state vector X=(X i(t), i=1, 2, ..., F_number) represents, wherein, i is the node that the vehicle will serve, X i (t) is the loadable capacity of the current vehicle; the objective function Y i =F(X i (t)) determines the food concentration at the current location of the artificial fish; the distance between individual artificial fish is expressed as d i,i+1 =‖X i -X i+1 ‖; For the VRPB problem, the initial position of the artificial fish needs to be placed on the starting point and the ending point, because the vehicle is only valid if it starts from the starting point and reaches the end point, or returns to the starting point from the end point.
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