Method for goods distribution based on optimized genetic algorithm

Abstract

According to the vehicle scheduling method designed by the invention, KMEANS algorithm optimization is carried out before chromosome coding; the poor locality search capability is preliminarily weakened; and precocity is easily generated. A brand new coding mode is adopted to reduce the coding redundancy,convergence speed is further accelerated, in addition, a new fitness function is also designed; differential amplification selection operation is adopted, manual adjustment and variation operation are carried out after intersection, no intersection route is generated on the whole, when one target distribution point is completed, the route process of the next target distribution point is directly entered, no redundant route exists in the whole process, the standard of the optimal solution is achieved, and therefore shorter-distance route distribution can be obtained.

Description

technical field [0001] The invention relates to a method for dispatching goods distribution, in particular to a method for dispatching and dispatching goods based on improved chromosome coding and improved fitness function. Background technique [0002] The transportation scheduling problem can affect the distribution service quality and distribution cost of enterprises. Optimized transportation scheduling speeds up delivery, reduces delivery costs, improves service quality, and increases corporate profits. Getting merchandise to customers on time and efficiently depends on proper vehicle scheduling. Generally speaking, the scheduling plan that decision makers need to formulate includes: the allocation of cargo vehicles, the selection of delivery routes, the selection of delivery time slots, and so on. [0003] However, if the distribution customers are many and scattered, and the distribution road is complicated, it is impossible to formulate a reasonable scheduling plan ...

AI Technical Summary

Problems solved by technology

[0004] The vehicle routing problem is a non-deterministic polynomial problem, which is difficult to obtain an exact solution

[0007] 2) The customer's order cannot be delivered in batches, each customer's order must be delivered by one vehicle

[0015] (5) Problem with time window and problem without time window

Although the genetic algorithm can solve the traditional polynomial solution problem of logistics distribution, the algorithm has poor local search ability and is prone to premature problems.

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