Population intelligent dynamic logistics knapsack optimization method

Abstract

The invention relates to a population intelligent dynamic logistics knapsack optimization method. The method comprises a dynamic logistics knapsack comprehensive optimization problem in logistics distribution and a solving method thereof. The invention discloses a dynamic logistics knapsack optimization problem. the dynamic path planning is combined with the knapsack problem; According to the dynamic logistics knapsack comprehensive optimization method and device, the purpose of comprehensively optimizing the knapsack value rate of the vehicle while optimizing the vehicle distribution path isachieved, the backpack problem is solved, the vehicle loading model is converted into the knapsack value optimization model, the loading optimization rate model of the logistics distribution vehicle can be properly simplified, and the dynamic logistics knapsack comprehensive optimization problem is easier to solve. The group intelligent optimization algorithm is a grey wolf optimization algorithm.The grey wolf optimization algorithm belongs to a biomimetic algorithm, the algorithm is commonly used for solving the combination optimization problem, the grey wolf optimization algorithm has a group learning mechanism, local optimization and global optimization can be balanced, and the defect that an existing heuristic algorithm cannot give consideration to local optimization and global optimization is overcome. A delivery scheme obtained by solving the comprehensive optimization problem shows that by adopting the method provided by the invention, the vehicle delivery distance and the vehicle load rate can be better and comprehensively optimized. Meanwhile, data experiments prove that the dynamic logistics knapsack comprehensive optimization problem is suitable for large-scale logistics distribution optimization scenes.

Description

technical field [0001] The invention relates to technical fields such as dynamic path planning, knapsack optimization, artificial intelligence, logistics distribution optimization, etc., and in particular relates to a dynamic logistics knapsack optimization problem and an optimization method thereof. Background technique [0002] The path planning problem is a hot issue in the field of operations research and combinatorial optimization, and the research on dynamic path planning originated in the 1970s. This problem is based on vehicle path planning, and on the basis of planning vehicle routes, other factors are reasonably considered, such as Traffic, customer service quality, exceptions, etc. to meet changing delivery needs, making the model more applicable. The existing dynamic factors include customer dynamic demand, uncertain information, random travel time, customer satisfaction, time window and so on. The knapsack problem (KP) is also a typical combinatorial optimizati...

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Problems solved by technology

Correspondingly, considering that the existing heuristic algorithm cannot take into account the shortcomings of local optimization and global optimization when solving combinatorial optimization problems, the gray wolf optimization algorithm adopted in the present invention can take into account both local optimization and global optimization, so as to solve the comprehensive optimization of dynamic logistics knapsack problem, get a better terminal distribution plan

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