Authors: Nikica Peric, Slaven Begovic, Vinko Lesic

Published on: March 07, 2024

Impact Score: 7.4

Arxiv code: Arxiv:2403.04420

Summary

• What is new: Introduction of a new procedure based on adaptive memory metaheuristic combined with local search for the vehicle routing problem, addressing real-world complexities.
• Why this is important: Optimisation of vehicle routes in real industrial applications is complex due to the need for prompt execution of complex combinatorial algorithms.
• What the research proposes: A new procedure utilizing the Clarke-Wright algorithm with added stochasticity through a dropout factor, combined with adaptive memory metaheuristic and local search.
• Results: Achieved an average savings of 2.03% in delivery time and 20.98% in total delivery costs compared to state-of-the-art algorithms.

Technical Details

Technological frameworks used: Adaptive memory metaheuristic combined with local search

Models used: Clarke-Wright algorithm with dropout factor

Data used: Existing benchmarks and real industrial case study

Potential Impact

Logistics companies, delivery services, and transport sectors could greatly benefit from the insights, potentially improving efficiency and reducing operational costs.

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