Multi-vehicle cooperative carpooling path optimization method based on improved fruit fly algorithm

A path optimization and fruit fly algorithm technology, applied in the field of intelligent transportation, can solve problems such as the difficulty of traveling by taxi, achieve the effect of improving diversity, reducing seat vacancy rate, and enhancing the ability to escape from local optimum

Pending Publication Date: 2019-08-02
HENAN INST OF SCI & TECH
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  • Abstract
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The technical problem solved by the present invention is to provide a multi-vehicle collaborative carpooling route optimization method based on the improved fruit fly algorithm, which can effectively solve the problem of people’s difficulty in taking a taxi when the traffic in the city is restricted, and promote the urban traffic direction. The further development of intelligence will eventually enable taxis or private cars to carry more passengers, increase the occupancy rate, reduce empty driving and fuel consumption, and effectively alleviate the current situation of difficult taxis and traffic congestion

Method used

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  • Multi-vehicle cooperative carpooling path optimization method based on improved fruit fly algorithm
  • Multi-vehicle cooperative carpooling path optimization method based on improved fruit fly algorithm
  • Multi-vehicle cooperative carpooling path optimization method based on improved fruit fly algorithm

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Embodiment 1

[0044] see figure 1 , the method for solving the multi-vehicle cooperative carpool route optimization problem proposed by the present invention, its specific steps are as follows:

[0045] 1. Establish goals and establish optimization models

[0046] The symbols used in this example to solve the multi-vehicle collaborative carpooling route optimization problem are as follows:

[0047] C: Taxi collection;

[0048] N: the number of people in the taxi;

[0049] R: the collection of paths for taxis to complete carpooling orders;

[0050] D: The location of the taxi and the collection of departure and destination associated with the passenger order;

[0051] S ir : Binary decision variable, indicating whether the i-th passenger is in the sub-path r, i∈D, r∈R;

[0052] h ijr : Binary decision variable, indicating whether the taxi transports passenger i and passenger j continuously in the rth sub-path, i, j∈D, r∈R;

[0053] d ij : the distance between the location of the tax...

Embodiment 2

[0076] In this embodiment, in combination with the route optimization problem of multi-vehicle cooperative carpooling in a taxi company, the present invention is used to find the optimal solution or suboptimal solution that satisfies the constraint conditions.

[0077] 1. Problem overview

[0078] According to the above technical solution, a certain taxi company is used as an example for illustration. Randomly generate 27 passenger orders for testing. The distance between the location of the taxi and the origin of the passenger, as well as the distance between the origin and destination of the passenger and the origin and destination of other passengers obeys the uniform distribution on [5km, 20km]. The nuclear load N of the taxi is 4. The experiment was carried out on the Win10 system platform, Intel processor with 3.7GHz main frequency, 4GB memory and Matlab R2014b development environment.

[0079] 2. Comparison with other evolutionary algorithms

[0080] In order to ver...

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Abstract

The invention discloses a multi-vehicle cooperative carpooling path optimization method based on an improved fruit fly algorithm in the technical field of intelligent transportation. The key points ofthe technical scheme are as follows: through a step length sine attenuation strategy, an algorithm can carry out breadth exploration on a solution space with a large step length in the early evolution stage and carry out deep development with a small step length in the later evolution stage, and meanwhile, due to the fact that the step length is attenuated in a sine oscillation manner, the performance of the algorithm can be well considered in global and local optimization; and through a chaotic variation strategy, diversity of populations is improved, and the capability of jumping out of local optimum is further improved. The improvement measures further improve the solving performance of the drosophila melanogaster algorithm. The efficiency of citizen carpooling travel is effectively improved, expenses are saved for passengers, benefits are increased for drivers, and more importantly, the emission of automobile exhaust is reduced, and the air quality is improved.

Description

technical field [0001] The invention belongs to the technical field of intelligent transportation, and in particular relates to a multi-vehicle cooperative carpooling route optimization method based on an improved fruit fly algorithm. Background technique [0002] With the increase in the number of migrants and the introduction of measures to restrict the use of motor vehicles with odd and even numbers, the difficulty of hailing a taxi has become more prominent. With the number of taxis saturated, carpooling will become an effective solution to this livelihood problem that plagues people's normal travel. In this context, the research on the route optimization of taxi multi-vehicle collaborative carpooling business has a very good role in promoting energy saving and emission reduction and improving public travel efficiency. Therefore, for the route optimization problem of multi-vehicle cooperative carpooling, it is of great scientific significance and social value to seek an...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/02G06Q10/04G06N3/00G06Q50/30
CPCG06Q10/025G06Q10/047G06N3/006G06Q50/30
Inventor 杨文强宋长源孔晓红李晓娟徐君鹏付广春张素君
Owner HENAN INST OF SCI & TECH
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