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- W4386858596 abstract "Planning and optimizing logistics distribution routes is a challenging problem in logistics industry. Particle swarm optimization (PSO) has been widely used to solve vehicle scheduling problems due to its excellent global search ability and parallel computing advantages. However, challenges such as premature convergence and balancing global and local search abilities through inertia weight adjustment strategies need to be improved. This paper proposes a particle swarm optimization method based on arctangent adaptive inertia weight (ATWPSO) by introducing the arctangent function to improve the weight adjustment strategy, which allows the inertia weight to fit the current search state adaptively. We validate ATWPSO using the vehicle routing problems with time windows (VRPTW) benchmark dataset. The results show that ATWPSO reduces the total travel distance by an average of 13.2% and 12.0%, respectively, compared to SRWPSO and MAWPSO. Therefore, ATWPSO can significantly reduce logistics enterprise costs and improve delivery efficiency." @default.
- W4386858596 created "2023-09-20" @default.
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- W4386858596 date "2023-04-21" @default.
- W4386858596 modified "2023-09-27" @default.
- W4386858596 title "Arctangent Adaptive Inertia Weight Particle Swarm Optimization for Logistics Distribution Route Planning" @default.
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- W4386858596 doi "https://doi.org/10.1109/icsp58490.2023.10248666" @default.
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