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- W2112947395 abstract "This article establish an efficient electronic commerce logistics operation system to reduce distribution costs and build a logistics network operation model based on around the B2C electronic commerce enterprise logistics network operation system. B2C electronic commerce transactions features in the enterprise network platform. To solve the NP-hard problem this article use hybrid ant colony algorithm, particle swarm algorithm and group swarm intelligence algorithm to get a best solution. According to the intelligent algorithm, design of electronic commerce logistics network optimization system, enter the national 22 electronic commerce logistics network for validation. Through the experiment to verify the optimized logistics cost greatly decreased. This research can help B2C electronic commerce enterprise logistics network to optimize decision-making under the premise of ensuring the interests of consumers and service levels also can be an effective way for enterprises to improve the efficiency of logistics services and reduce operation costs" @default.
- W2112947395 created "2016-06-24" @default.
- W2112947395 creator A5088731741 @default.
- W2112947395 date "2013-09-10" @default.
- W2112947395 modified "2023-09-25" @default.
- W2112947395 title "Electronic Commerce Logistics Network Optimization Based on Swarm Intelligent Algorithm" @default.
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- W2112947395 doi "https://doi.org/10.4304/jnw.8.9.2163-2170" @default.
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