Abstract
In many transport companies, one of the main objectives is to optimize the travel cost of their fleet. Other objectives are related to delivery time, fuel savings, etc. However warehouse stock management is not properly considered. Warehouse stock control is based on the correct allocation of resources to each order. In this paper, we combine the warehouse stock management problem and the routing problem to be applied in a real company that allows negative stock in their warehouses. The proposed multi-objective problem is modeled and solved by the greedy randomized adaptive search (GRASP) algorithm. The results shows that the proposed algorithm outperforms the current search technique used by the company mainly in stock balancing, improving the negative average stock by up to 82%.
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The paper has been partially funded by the Spanish research project TIN2016-80856-R.
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Perez, C., Salido, M.A., Gurrea, D. (2020). A Metaheuristic Search Technique for Solving the Warehouse Stock Management Problem and the Routing Problem in a Real Company. In: Bramer, M., Ellis, R. (eds) Artificial Intelligence XXXVII. SGAI 2020. Lecture Notes in Computer Science(), vol 12498. Springer, Cham. https://doi.org/10.1007/978-3-030-63799-6_15
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DOI: https://doi.org/10.1007/978-3-030-63799-6_15
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