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Hybrid arithmetic optimization algorithm for a new multi-warehouse joint replenishment and delivery problem under trade credit

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Abstract

Trade credit is a significant form of short-term financing in the real business situation. This study proposes a practical multi-warehouse joint replenishment and delivery (MJRD) problem under trade credit in accordance with the realistic situation. The goal of the MJRD is to find the reasonable basic replenishment cycle time, the joint replenishment frequency, the delivery frequency, and the assignment information of suppliers to minimize the total cost. Five intelligent algorithms, which include a differential evolution algorithm, genetic algorithm, adaptive hybrid differential evolution algorithm, arithmetic optimization algorithm (AOA), and hybrid arithmetic optimization algorithm (HAOA), are designed to find a solution to this MJRD problem under trade credit. The results of several experiments show that HAOA is effective in solving the proposed MJRD. Compared with AOA, the best improvement is 46.66%. HAOA is a satisfactory algorithm for the proposed MJRD under trade credit.

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Data Availability

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

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Funding

This research is partially supported by National Social Science Foundation of China (No. 20&ZD126), National Natural Science Foundation of China (No.72172112; 71810107003), and Fundamental Research Funds for the Central Universities (WUT: 2022IVA067).

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Authors and Affiliations

  1. School of Management, Wuhan University of Technology, Wuhan, 430070, Hubei, China

    Lu Peng

  2. School of Management, Huazhong University of Science and Technology, Wuhan, 430074, Hubei, China

    Lin Wang & Sirui Wang

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  1. Lu Peng
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  2. Lin Wang
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  3. Sirui Wang
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Correspondence to Sirui Wang.

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Peng, L., Wang, L. & Wang, S. Hybrid arithmetic optimization algorithm for a new multi-warehouse joint replenishment and delivery problem under trade credit. Neural Comput & Applic 35, 7561–7580 (2023). https://doi.org/10.1007/s00521-022-08052-0

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