Task package optimization method, system and device
An optimization method and wrapping technology, applied in the fields of instruments, character and pattern recognition, data processing applications, etc., can solve the problems of limited algorithm computing power, inability to find destructive formula, poor quality of solutions, etc., to achieve fast planning paths and simple structure. , the effect of reduced computing power requirements
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Embodiment 1
[0046] This embodiment provides a task package optimization method, including:
[0047] S1. Obtain the attribute information of multiple packages, the attribute information is address flow, packaging requirements and time window, where the address flow is the start and end address of the package, packaging requirements such as whether the package needs to be placed forward, and the time window is the customer Shipping time and requested delivery time;
[0048] S2. Establish a corresponding multi-dimensional vector according to the package attribute information, the multi-dimensional vector is address flow direction, packaging requirements and time window;
[0049] S3. Input the multi-dimensional vector into the k-means clustering algorithm to classify the parcels, wherein the parcels of the same classification group are input into the large-scale neighborhood search algorithm as a whole for path planning,
[0050] The specific steps are:
[0051] S31. Randomly select K vecto...
Embodiment 2
[0077] The features of this embodiment that are the same as those of Embodiment 1 will not be described in detail. The features of this embodiment that are different from Embodiment 1 are:
[0078] In the task package optimization method of this embodiment,
[0079] In step S1, the attribute information is the address flow direction, packaging requirements and time window, where the address flow direction is the start and end addresses of the package, the packaging requirements are such as pasting fragile instructions, and the time window is the customer’s mailing time and required delivery time;
[0080] Step S2: Establish a corresponding multi-dimensional vector according to the package attribute information, the multi-dimensional vector is address flow, packaging requirements and time window.
[0081] The selected number of cluster centers K=0.1×the total number of packages.
Embodiment 3
[0083] The features of this embodiment that are the same as those of Embodiment 1 will not be described in detail. The features of this embodiment that are different from Embodiment 1 are:
[0084] In the task package optimization method of this embodiment,
[0085] In step S1, the attribute information is the address flow, packing requirements and time window, wherein, the address flow is the starting and ending address of the package, the packing requirements such as commodity price labels are affixed to the outside of the package, and the time window is the delivery time and delivery time required by the customer. arrival time;
[0086] Step S2: Establish a corresponding multi-dimensional vector according to the package attribute information, the multi-dimensional vector is address flow, packaging requirements and time window.
[0087] The selected number of cluster centers K=0.8×the total number of packages.
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