Evolutionary hybrid search for optimization in transport logistics information systems

This paper addresses real-world agricultural transport logistics optimization in Uzbekistan, focusing on physical loading constraints and their impact on route efficiency. The study analyzes routing challenges specific to agricultural transportation – including vehicle capacity, delivery deadlines, and Last-In-First-Out (LIFO) loading requirements. Field measurements demonstrate that vibration exposure significantly affects product quality, with damage rates varying from 2-35 % depending on road conditions. A hybrid optimization approach combining differential evolution, genetic algorithms, and local search is proposed and validated using real operational data. Experiments on 450 delivery requests show 14.3 % distance reduction and 46 % reduction in product damage. The system achieves return on investment within 2.3 months with measurable improvements in transport efficiency and product quality preservation.

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