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- W2912451127 abstract "In this paper, we propose a novel ant colony optimization algorithm based on improved brainstorm optimization (IBSO-ACO) to solve the vehicle routing problem with soft time windows. Compared with the traditional ant colony algorithm, the proposed IBSO-ACO can better address the local optimum problem, since we have carefully designed an improved brainstorming optimization algorithm to update the solutions obtained by the ant colony algorithm, which enhance the solution diversity and the global search ability. Furthermore, we use the classification method to accelerate the convergence of the proposed algorithm. The extensive experimental results have confirmed that the proposed IBSO-ACO algorithm can achieve a lower routing cost at a high convergence rate than the traditional ant colony algorithm and the simulated annealing ant colony algorithm." @default.
- W2912451127 created "2019-02-21" @default.
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- W2912451127 date "2019-01-01" @default.
- W2912451127 modified "2023-10-14" @default.
- W2912451127 title "Brainstorming-Based Ant Colony Optimization for Vehicle Routing With Soft Time Windows" @default.
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- W2912451127 doi "https://doi.org/10.1109/access.2019.2894681" @default.
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