Abstract
Efficient operational planning of transportation is crucial in longdistance traffic, where the coordination of shipments plays a pivotal role in optimizing logistics operations. This article presents an algorithm designed to streamline the planning process for machine shipments in long-distance transportation. The algorithm leverages advanced optimization techniques and machine learning to address the complexities associated with route selection, scheduling, and resource allocation.
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