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Multi-type harvester cooperative scheduling optimization method based on improved whale algorithm

A technology of collaborative scheduling and optimization methods, applied in computing, computing models, biological models, etc.

Pending Publication Date: 2019-07-30
HENAN INST OF SCI & TECH
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  • Abstract
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  • Claims
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Problems solved by technology

Zhang et al. (Suitability selection of emergency allocation algorithm for agricultural machinery cross-regional operations, Journal of Agricultural Engineering, 2018) studied the optimization problem of agricultural machinery cross-regional emergency operation allocation, and proposed two types of agricultural machinery cross-regional based on the closest priority and the largest contribution priority The emergency operation allocation algorithm, the scholar also did not conduct research on multiple types of agricultural machinery

Method used

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  • Multi-type harvester cooperative scheduling optimization method based on improved whale algorithm
  • Multi-type harvester cooperative scheduling optimization method based on improved whale algorithm
  • Multi-type harvester cooperative scheduling optimization method based on improved whale algorithm

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Experimental program
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Embodiment 1

[0056] see figure 1 , the multi-type harvester cooperative scheduling optimization method based on the improved whale algorithm proposed by the present invention, its specific steps are as follows:

[0057] 1. Establish goals and establish optimization models

[0058] The symbols used in this example to solve the multi-type harvester cooperative scheduling optimization problem are as follows:

[0059] C: collection of harvesters;

[0060] R: The harvester completes the path collection of all harvesting tasks;

[0061] D: The location of the harvester and the collection of plots to be harvested;

[0062] S ir : Binary decision variable, indicating whether the i-th plot is in the sub-path r, i∈D, r∈R;

[0063] h ijr : Binary decision variable, indicating whether the harvester continuously harvests plot i and plot j in the rth sub-path, i, j∈D, r∈R;

[0064] d ij : the distance from the harvester to the plot and from the plot to the plot, i,j∈D;

[0065] the s i : the a...

Embodiment 2

[0089] This embodiment solves the multi-type harvester cooperative scheduling optimization problem in combination with multi-type plots of an agricultural cooperative, and uses the present invention to find the optimal solution or suboptimal solution that meets the constraint conditions.

[0090] 1. Problem overview

[0091] According to the above technical solution, an agricultural cooperative is used as an example to illustrate the application background. The agricultural cooperative has 6 types of harvesters, and there is only one harvester of each type. The relevant parameters of the harvesters are shown in Table 1. 30 wheat plots were randomly generated for testing, and the plot sizes are shown in Table 2. The distance between the location of the harvester and the plot, and the distance between the plot and the plot obeys the uniform distribution on [0km, 5km]. The experiment was carried out on the Win10 system platform, Intel processor with 3.7GHz main frequency, 4GB me...

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Abstract

The invention discloses a multi-type harvester cooperative scheduling optimization method based on an improved whale algorithm, and belongs to the technical field of agricultural mechanical equipmentresource optimization configuration. The key points of the technical scheme are as follows: a convergence factor adaptive change strategy is introduced, and non-elite individual historical informationcompletely participates in the variation strategy; that is to say, through self-adaptive change of the convergence factor, the algorithm can keep a relatively strong global exploration capability anda relatively fast convergence speed at a relatively large step length in the early evolution stage, and perform deep development at a relatively small step length in the later evolution stage, so that the quality of a solution is improved; all historical parent individual information of continuous 10 generations of non-evolved individuals participates in a mutation strategy, and the historical information of the individuals participates in mutation, so that the diversity of populations can be quickly improved, and the algorithm jumps out of local optimum. The working efficiency of the harvester is effectively improved, a good reference is provided for intelligent dispatching of the harvester, and meanwhile further development of agricultural intelligent equipment is promoted.

Description

technical field [0001] The invention belongs to the technical field of optimal allocation of agricultural machinery and equipment resources, and in particular relates to an optimization method for cooperative scheduling of multi-type harvesters based on an improved whale algorithm. Background technique [0002] The vigorous development of agricultural cooperatives has given birth to agricultural machinery service companies, which rely on agricultural machinery (such as: harvesters) to provide field operations services for agricultural cooperatives. Due to the large area of ​​cultivated land contracted by agricultural cooperatives and the complex types of land plots, in order to improve the efficiency of agricultural machinery field operations, it is necessary to optimize the coordinated scheduling of multi-type agricultural machinery suitable for different types of land plots. In this context, the research on the multi-type harvester cooperative scheduling optimization probl...

Claims

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Application Information

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IPC IPC(8): G06Q10/04G06Q50/02G06N3/00
CPCG06Q10/04G06Q50/02G06N3/006
Inventor 杨文强孔晓红李晓娟秦国庆陈艳锋付广春张素君徐君鹏郭昊
Owner HENAN INST OF SCI & TECH
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