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The organization of the order picking process has the greatest impact on the efficiency of the warehouse or distribution center, and thus on the supply chain efficiency. From the moment of accepting the customer's order through its completion to the time of shipment, there are many possibilities of making mistakes and errors both in terms of accuracy and completeness, as well as time-wasting. The paper presents the problem of order-picking in a typical warehouse in which items must be collected manually by the workers available in a given period of time (e.g. working shift). The goal is to develop a plan that minimizes the number of pickers that must be involved in picking orders in a given section of a warehouse and simultaneously optimizes the distance covered by the pickers. Mixed integer programming model for the order-picking and route planning problem is formulated and the heuristic based on genetic algorithm and TSP r-opt technique is proposed to solve it. Proposed genetic algorithm uses a crossover dedicated to the special representation of the solution coding order-picking plan and four different mutations allowing for extensive exploration of solution space resulting in a high quality, reliable order-picking plan. The quality of the proposed solution is evaluated against the data coming from one of the real warehouses. It was possible to achieve a significant reduction in the number of pickers necessary to collect all items as well as the total distance covered by the pickers.
Keywords: order-picking, route planning, warehouse, optimization, heuristic© This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.