A Double-layer Optimization Algorithm for Multi-direction Intermodal Transportation Scheduling for Cigarette Delivery
A double-layer optimization and multi-directional technology, applied in the field of cigarette logistics, can solve the problems of infeasible solution of network convergence, poor parameter robustness, etc., and achieve the effect of dynamic scheduling of multiple storage points and multiple directions
Active Publication Date: 2022-07-08
HONGYUN HONGHE TOBACCO (GRP) CO LTD
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[0005] (2) The network may converge to an infeasible solution to the problem;
[0006] (3) The final result of network optimization depends largely on the parameters of the network, that is, the parameters are less robust
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[0045] In order to facilitate those skilled in the art to understand and implement the present invention, the technical solutions of the present invention will now be further described with reference to the accompanying drawings and specific embodiments.
[0046] At the same time, since the traditional Hopfield network still adopts the gradient descent strategy, the vehicle path optimization calculation based on the Hopfield network usually leads to the following problems:
[0047] (1) The network eventually converges to a local minimum solution, rather than the global optimal solution of the problem;
[0048] (2) The network may converge to an infeasible solution to the problem;
[0049] (3) The final result of network optimization largely depends on the parameters of the network, that is, the parameter robustness is poor.
[0050] In order to solve the above shortcomings of traditional Hopfield neural network and make the algorithm more suitable for solving the hierarchical...
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A double-layer optimization algorithm for multi-depot and multi-directional intermodal transport scheduling for cigarette delivery belongs to the field of cigarette logistics. The multi-depot and multi-directional intermodal transport scheduling for cigarette delivery is improved by introducing a simulated annealing algorithm and a Levy flight strategy. Hopfield neural network algorithm (IHNN) is used as a global optimization algorithm to form a method for intermodal transportation scheduling of cigarette finished products based on improved Hopfield neural network algorithm. At the same time, combined with the application of order pool dynamic programming algorithm, order pool stowage optimization and optimal vehicles are carried out. Select the planning algorithm to select the distribution vehicle, and realize the dynamic scheduling of multiple warehouse points and multiple directions. The invention solves the multi-depot multi-direction vehicle scheduling problem, which is a multi-objective complex vehicle routing problem for dynamic order arrival, which is also the core problem faced by the finished product logistics warehousing operation scheduling optimization of tobacco industry enterprises.
Description
technical field [0001] The invention relates to the field of cigarette logistics, and more particularly to a double-layer optimization algorithm for multi-direction and multi-direction intermodal transport scheduling for cigarette delivery. Background technique [0002] Particle swarm optimization algorithm and whale optimization algorithm have been widely used in the field of vehicle scheduling, and have achieved good results, but there are also some problems. The whale optimization algorithm has the difficulty of coordinating exploration and development capabilities, and it is easy for the population to fall into local optimum prematurely. insufficient. For the tobacco logistics scheduling problem, its solution scale is large and the feasible region is small, and the traditional whale optimization algorithm shows weak search ability. [0003] At the same time, since the traditional Hopfield network still adopts the gradient descent strategy, the vehicle path optimization ...
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IPC IPC(8): G06Q10/04G06N3/00G06N3/04G06N3/08G06Q10/06G06Q10/08
CPCG06Q10/04G06Q10/06315G06Q10/087G06N3/08G06N3/006G06N3/045Y02T10/40
Inventor 安裕强徐跃明欧阳世波陈晓伟王磊迟文超谢俊明李柏宇余丽莎王康王鹍秦希
Owner HONGYUN HONGHE TOBACCO (GRP) CO LTD