Shared bicycle optimal scheduling method based on genetic ant colony fusion algorithm

A technology for sharing bicycles and optimizing scheduling, which is applied in the field of urban shared transportation and can solve problems such as unbalanced distribution of shared bicycles

Inactive Publication Date: 2019-07-05
ZHENGZHOU UNIV
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Problems solved by technology

[0009] The purpose of the present invention is to provide a shared bicycle optimization scheduling method based on the genetic ant colony fusion algorithm, which can effectively solve the problem of unbalanced distribution of large-scale non-stop shared bicycles, and optimize the total travel distance of the dispatched vehicle route and the minimum Scheduling Completion Time

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  • Shared bicycle optimal scheduling method based on genetic ant colony fusion algorithm
  • Shared bicycle optimal scheduling method based on genetic ant colony fusion algorithm
  • Shared bicycle optimal scheduling method based on genetic ant colony fusion algorithm

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Embodiment Construction

[0058] Such as figure 1 Shown, the present invention comprises the following steps:

[0059] A. Collect shared bicycle data points in the area to be tested;

[0060] B. Use the K-means clustering algorithm to divide the shared bicycle data points into N clusters, each cluster includes M sites, and define the distance cluster T k The nearest station to the center is the cluster node Θ k , 1≤k≤M;

[0061] C. According to the number of bicycles in each cluster, perform cluster repair on each cluster; cluster T k The repair process is as follows:

[0062] c1: Get the number of bicycles required in each cluster is a positive number, it means that the number of supplementary bicycles in the cluster is is a negative number, it means that the number of bicycles that the cluster node needs to transport is

[0063] c2: Judgment Whether the calculation result is greater than 1, if greater than 1, then enter step c3, otherwise directly enter step D; V represents the dispa...

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Abstract

The invention discloses a shared bicycle optimal scheduling method based on a genetic ant colony fusion algorithm. The method comprises: using a K-means clustering algorithm to gather the data pointsof the bicycles, considering the stock of the bicycles; then, obtaining an initial solution for connecting each node by using a genetic algorithm; the method comprises the steps of obtaining the number of stations in each cluster, calculating the sequence of scheduled vehicles passing through cluster nodes by using an ant colony algorithm, determining the number of loaded and unloaded bicycles foreach node, finally obtaining the shortest path for connecting the stations in each cluster by using the ant colony algorithm, equally dividing the number of unbalanced bicycles of the cluster, and completing a small-range scheduling strategy in the cluster. According to the method, the problem of unbalanced distribution of large-scale non-station shared bicycles is effectively solved, the total travel distance of vehicle scheduling routes is optimized, and the scheduling completion time is minimized.

Description

technical field [0001] The invention relates to the technical field of urban shared traffic, in particular to a shared bicycle optimization scheduling method based on a genetic ant colony fusion algorithm. Background technique [0002] With the rapid development of the sharing economy, non-stop shared bicycles are gradually popularized and promoted in China. With its advantages of convenience, environmental protection, and low price, it has quickly won the favor of consumers. Compared with traditional station-based shared bicycles, non-stop shared bicycles save start-up costs, avoid the construction of expensive docking stations, and increase the utilization rate of shared bicycles. However, the random use behavior of users leads to an imbalance in the spatial distribution of bicycles. [0003] Bike-sharing systems have exploded in popularity over the past decade, first in Western Europe and East Asia, and more recently in North America. Research on bike-sharing systems is...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q10/06G06Q50/30G06N3/00G06N3/12
CPCG06N3/006G06N3/126G06Q10/04G06Q10/06315G06Q50/30
Inventor 梁岩李林玉王靓徐小本何魏莉杨富强
Owner ZHENGZHOU UNIV
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