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- W4298394016 abstract "The population-based ant colony optimization (P-ACO) algorithm is a variant of the ant colony optimization metaheuristic specifically designed to address dynamic optimization problems. Whenever a change in the environment occurs, P-ACO repairs the pheromone trails affected by the change using previous solutions maintained in a population-list. Typically, change-related information are utilized for repairing these solutions. The change-related information for this dynamic vehicle routing problem (DVRP) case are the nodes removed and inserted when a change in the environment occurs. In this chapter, the operators of the unstringing and stringing (US) heuristic are utilized for repairing the solutions. Experimental results demonstrate that P-ACO embedded with the US heuristic outperforms other peer methods in a series of DVRP test cases." @default.
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- W4298394016 date "2022-10-02" @default.
- W4298394016 modified "2023-09-26" @default.
- W4298394016 title "Applying the Population-Based Ant Colony Optimization to the Dynamic Vehicle Routing Problem" @default.
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- W4298394016 doi "https://doi.org/10.1007/978-3-031-09835-2_20" @default.
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