Parallel computing-based logistics transportation scheduling method, device and equipment
A parallel computing and scheduling method technology, applied in logistics, computing, instruments, etc., can solve problems such as weak convergence ability, low running speed, low optimization efficiency, etc., to improve robustness, stability, and running speed Faster, better results for search capabilities
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Embodiment 1
[0048] The following is an introduction to Embodiment 1 of a logistics transportation scheduling method based on parallel computing provided by the present application, see figure 1 , embodiment one includes:
[0049] Step S101, calling the main thread to obtain the logistics transportation scheduling model and multiple parallel sub-threads;
[0050] Step S102, calling each of the parallel sub-threads, performing an explosion operation and a Gaussian mutation operation based on the current fireworks population according to the fireworks algorithm, and determining the optimal fireworks of the parallel sub-threads in the current iteration process according to the target fitness function;
[0051] Step S103, if the current number of iterations does not reach the maximum number of iterations, call each of the parallel sub-threads to obtain the optimal fireworks of other parallel sub-threads, and update its own fireworks population according to the multi-group coordination strategy...
Embodiment 2
[0057] see figure 2 , embodiment two specifically includes:
[0058] Step S201, initialization control parameters, main thread and PN sub-threads;
[0059] Concrete, control parameter initialization is as follows in the present embodiment: client point quantity is n, the maximum number of iterations is 1 max , iteration counter I (initial 0), number of parallel threads PN, population size of fireworks is N, number of explosion sparks S sum , Firework explosion radius A, Gaussian variation spark number GM, Firework random key area upper limit R up with lower limit R down , the number of parallel exchange iterations I Pmax , Parallel communication parameter α, multi-cooperative group iteration number I Mmax , multi-group random deviation ratio η, main group deviation ratio β, slave group deviation ratio γ, and constant ε.
[0060] Step S202, for each sub-thread, call it to initialize the fireworks population, determine the fitness value of each fireworks in the fireworks ...
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