A courier group path navigation method

Abstract

The invention discloses a courier group path navigation method, belongs to the technical field of path navigation, and aims to solve the multi-point and multi-target navigation problem of logistics distribution. Due to the regionality of the logistics distribution point, the method enables the distribution path length of each courier to be as short as possible and approximately equal by reasonablyallocating a plurality of courier, so that all packages can quickly and effectively be received by the users as much as possible. Aiming at a plurality of indexes of group path navigation, the methodprovides a series of strategy improvements including a mean value rebound-state transition formula, the length of the path of each courier is manually controlled through a rebound warehouse point, sothat the length is shorter, and the uniformity is better; a multi-target assessment mode which enables the model to balance a plurality of different targets and adapt to actual model requirements; And a mode of searching different pheromone updating strategies at different stages by the ant colony. By adopting the method, the distribution paths of multiple couriers can be navigated in a unified manner, so that the labor cost is effectively reduced, and the distribution time is shortened.

Description

technical field [0001] The invention belongs to the field of route navigation, and in particular relates to a courier group route navigation method for multi-person and multi-target navigation. Background technique [0002] Driven by online shopping, the express service industry has developed rapidly. In the express logistics process, the most urgent problem to be solved is the last mile of express delivery, that is, how to rationally allocate all logistics resources under the regional distribution points. Logistics personnel, so that all packages can reach users as quickly and efficiently as possible. Only by solving the last mile problem reasonably and effectively can we meet the actual needs of making full use of human resources, improving logistics efficiency, and improving user experience. [0003] In the current research on the logistics distribution navigation problem, the multi-traveling salesman problem is a common model method to solve the route navigation. Many ...

AI Technical Summary

Problems solved by technology

However, these research methods only aim at the single goal of path length, and cannot take into account multiple goals, resulting in poor practical significance.

In order to solve the different indicators of actual needs, many multi-objective optimization algorithms have also been derived, such as the genetic algorithm of NSGA series and SPEA series; the multi-objective ant colony algorithm scheme proposed by Ariyasingha using m-ACO, etc., but the previous multi-objective optimization algorithm exists Two problems: one is that the model constructed based on the single traveling salesman problem does not conform to the actual situation of logistics distribution; the other is that the research or optimization of the uniformity index is not obvious

[0004] Obviously, the existing algorithm techniques such as genetic algorithm, particle swarm algorithm, ant colony algorithm, etc., have achieved remarkable results in solving the single-objective multi-traveling salesman problem or the multi-objective single-traveling salesman problem. There are two problems: the search efficiency is too low, and the practicability is limited; the search results are difficult to take into account multiple goals, making the actual meaning unsatisfactory

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