Abstract
AbstractIt is vital to improve the efficiency of urban distribution with severe traffic congestion problems. However, few studies on urban distribution consider the impact of road conditions, which leads to less instructive results to the real-world problems. This paper considers the real travel time of the vehicles to minimize the total distribution time. Furthermore, hybrid brain storm optimization and large neighborhood search algorithm (BSO-LNS) are designed to solve this problem. The experimental results show that the proposed BSO-LNS algorithm is superior to peer competitors. The optimized routes are easier to obtain the global optima, which is suitable for solving the urban distribution problem under such complex road conditions.KeywordsReal-time road conditionsUrban distributionCrawlerBrain storm optimizationLarge neighborhood search
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