Multi-temperature co-allocation path planning method based on enhanced multi-strategy spider bee algorithm

By introducing enhanced multi-strategy spider bee algorithm and flexible compartment technology in multi-temperature co-distribution path planning, the departure time and path are optimized, and the efficiency and cost of traditional methods in multi-temperature co-distribution are solved, and more efficient cold chain logistics management is achieved.

CN119721905AActive Publication Date: 2025-03-28HEFEI UNIV OF TECH
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Patent Information

Application Number
CN202510205716.3
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-02-25
Publication Date
2025-03-28
Estimated Expiration
2045-02-25

AI Technical Summary

Technical Problem

Traditional path optimization methods are difficult to effectively deal with time windows, order splitting and temperature control complexity in multi-temperature co-distribution, resulting in insufficient cost and efficiency of cold chain logistics.

Method used

A multi-temperature co-distribution path planning method based on the enhanced multi-strategy spider bee algorithm is adopted, combining the dynamic changes of flexible compartments and ambient temperatures to optimize the vehicle departure time and distribution path to minimize the total distribution cost and energy consumption.

Benefits of technology

By optimizing the departure time and path, the energy efficiency utilization rate of cold chain transportation is improved, the number of vehicles is reduced, and the full load rate and distribution efficiency of vehicles are improved.

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Abstract

The invention discloses a multi-temperature co-distribution path planning method based on an enhanced multi-strategy spider bee algorithm, which is applied to the technical field of multi-temperature co-distribution distribution in the field of logistics and supply chain management, and comprises the following steps: obtaining vehicle resources and customer demands and position information of a distribution center, and establishing a refrigeration cost calculation function based on the change of environment temperature; on the basis of the refrigeration cost calculation function, a multi-temperature co-allocation path planning model based on the flexible compartment and the environment temperature with the aim of minimizing the total distribution cost is constructed, and constraint conditions of the multi-temperature co-allocation path planning model are constructed on the basis of vehicle resources and customer information; and an enhanced multi-strategy spider bee algorithm combining chaotic mapping, a self-adaptive elite strategy and a reciprocating population reduction strategy is used for target solution of the model, and the optimal departure time and distribution path are obtained. The energy efficiency utilization rate in the cold chain transportation process is effectively improved, and the load factor of the vehicles is improved while the number of the used vehicles is minimized.
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