Solving an order batching, picker assignment, batch sequencing and picker routing problem via information integration

Modern supply chain systems require an effective scheduling scheme based on industrial information inte-gration. Warehouses are a key part of the supply chain systems. Its efficiency can be significantly improved by making full use of the multi-dimensional information in an order-picking process. This work presents an integrated order batching, picker assignment, batch sequencing, and picker routing problem in a warehouse. Its solution is difficult due to the coupling of various information such as diversity of orders, orderliness of picking positions, and complexity of a warehouse environment. In order to obtain a high-quality solution in a reasonable time, this work proposes a hybrid iterated local search algorithm embedded with heuristic rules. In it, multiple effective perturbation moves with an evolutionary mechanism are designed to allow it to escape from a local optimal region. A perturbation strategy based on its convergence speed is presented to balance exploration and exploitation. An acceptance criterion based on the Metropolis criterion is used to improve its global search ability. Besides, a routing strategy based on Manhattan distance is proposed to evaluate the performance of the proposed method. Finally, various simulation experiments and its comparisons with several existing methods are performed to validate its advantages. The impact of information integration on system performance is also investigated.