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View all- Yang FCao YZhang X(2023)Research on vehicle routing problem based on improved dragonfly algorithm2023 China Automation Congress (CAC)10.1109/CAC59555.2023.10451792(2549-2554)Online publication date: 17-Nov-2023
Research on Particle Swarm Optimization Algorithm with Jump Factor for Groupage Cargo Scheduling Problem
Pages 491 - 496
Abstract
In order to efficiently plan the routing of dispatching vehicles and satisfy all customers' routing demands with as little expenditure as possible, a multi-depot joint routing of dispatching vehicles (MDJGVRP) mathematical model with unsplit demands was established, and a new neighborhood adaptive particle swarm optimization algorithm with jump factor was proposed to solve the problem. In the iterative process of the algorithm, the optimal value stagnation problem is solved by constantly adjusting the particle search neighborhood and dynamically updating the jump factor, so as to effectively improve the ability of the algorithm to jump out of the local optimal value. Compared with the original particle swarm algorithm, artificial bee colony algorithm and bat algorithm, the size calculation example is verified that the algorithm has faster convergence speed and optimization ability.
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Published In
April 2022
1065 pages
ISBN:9781450395786
DOI:10.1145/3544109
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Publication History
Published: 18 July 2022
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IPEC2022
IPEC2022: 2022 3rd Asia-Pacific Conference on Image Processing, Electronics and Computers
April 14 - 16, 2022
Dalian, China
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View all- Yang FCao YZhang X(2023)Research on vehicle routing problem based on improved dragonfly algorithm2023 China Automation Congress (CAC)10.1109/CAC59555.2023.10451792(2549-2554)Online publication date: 17-Nov-2023
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