The modern distribution industry demands improved efficiency in logistics to lower prices while maintaining product quality. However, the efficiency of picking (collecting commodities in a warehouse), which accounts for a large percentage of the total logistics cost, has not improved significantly. In this study, we propose a traveling route derivation method that allows the warehouse layout to be set arbitrarily. Specifically, we combined the A* and genetic algorithms to reduce the walking distance of picking workers and improve picking efficiency in a warehouse. Furthermore, we simulated the route derivation for picking based on practical work, the walking distances were compared using a comparison method (brute-force method and without A* algorithm method), and the usefulness of the proposed method was evaluated.
The modern distribution industry demands improved efficiency of their logistics systems to lower prices while maintaining product quality. However, the efficiency of "picking", performing collection work in the racks in a warehouse, which accounts for a large percentage of the total cost of logistics, has not yet improved.In this study, we propose a traveling route derivation method that allows the warehouse layout to be set arbitrarily. Specifically, we have combined the A* and genetic algorithms to reduce the walking distance of picking workers to improve picking efficiency in a warehouse. Furthermore, we have simulated the route derivation during picking work by assuming practical work, compared the walking distances with the brute-force method, and evaluated the usefulness of the proposed method.
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