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The existing approaches to warehouse logistics processes optimization are predominantly aimed at single-warehouse systems. They do not encompass the interrelationship between strategic and operational decisions within multi-period and multi-level distribution networks. The isolated optimization of individual stages, such as order batching, picker routing, truck loading, leads to a decrease in the entire system overall efficiency. In this work, the issue of warehouse logistics processes optimization in contemporary multi-echelon systems was considered. An integrated mathematical model and a hybrid algorithm for order picking and routing under uncertainty were presented. A multi-objective problem with fuzzy parameters was formulated. It aimed at minimizing delivery time and total logistics costs. A step-by-step procedure solution for the issue of warehouse logistics processes optimization was proposed. In the first step the fuzzy model was transformed into a crisp one using a probabilistic method. In the second step a multi-criteria decision-making method and the Benders decomposition algorithm were applied. The local routing problem was solved by integrating the knapsack problem and the traveling salesman problem, while an improved ant colony optimization algorithm with Q-learning (Ant-Q) was applied for path optimization. According to experiments, the proposed algorithm has reduced the route length by 5–10 %, outperforming the standard CPLEX algorithm; the Benders decomposition application allows for the efficient solution of large-scale problems in linear time.

Key words: order picking, order consolidation, routing, uncertainty conditions, multi-echelon systems, Ant-Q, knapsack problem
Published in: INFORMATION-COMMUNICATION TECHNOLOGIES
Bibliography link: Portnov E. M., Si Thu Thant Sin. Method of managing consolidated logistics orders. Izv. vuzov. Elektronika = Proc. Univ. Electronics. 2026;31(2):365–371. (In Russ.). DOI: 10.24151/1561-5405-2026-31-2-365-371.QZQQAW

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UDK: 658.7:519.854.2
Publication type: Scientific article
Source lang: Russian
DOI: 10.24151/1561-5405-2026-31-3-365-371
RISC id: QZQQAW

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