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A novel differential evolution algorithm for joint replenishment problem under interdependence and its application

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  • Wang, Lin
  • He, Jing
  • Wu, Desheng
  • Zeng, Yu-Rong

Abstract

In this paper, we propose a new differential evolution (DE) algorithm for joint replenishment of inventory using both direct grouping and indirect grouping which allows for the interdependence of minor ordering costs. Since solutions to the joint replenishment problem (JRP) can be represented by integer decision variables, this makes the JRP a good candidate for the DE algorithm. The results of testing randomly generated problems in contrastive numerical examples and two extended experiments show that the DE algorithm provides close to optimal results for some problems than the evolutionary algorithm (EA), which has been proved to be an efficient algorithm. Moreover, the DE algorithm is faster than the EA for most problems. We also conducted a case study and application results suggest that the proposed model is successful in decreasing total costs of maintenance materials inventories significantly in two power companies.

Suggested Citation

  • Wang, Lin & He, Jing & Wu, Desheng & Zeng, Yu-Rong, 2012. "A novel differential evolution algorithm for joint replenishment problem under interdependence and its application," International Journal of Production Economics, Elsevier, vol. 135(1), pages 190-198.
    • Handle: RePEc:eee:proeco:v:135:y:2012:i:1:p:190-198
    DOI: 10.1016/j.ijpe.2011.06.015
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    4. Cui, Ligang & Deng, Jie & Liu, Rui & Xu, Dongyang & Zhang, Yajun & Xu, Maozeng, 2020. "A stochastic multi-item replenishment and delivery problem with lead-time reduction initiatives and the solving methodologies," Applied Mathematics and Computation, Elsevier, vol. 374(C).
    5. Sina Shaffiee Haghshenas & Behrouz Pirouz & Sami Shaffiee Haghshenas & Behzad Pirouz & Patrizia Piro & Kyoung-Sae Na & Seo-Eun Cho & Zong Woo Geem, 2020. "Prioritizing and Analyzing the Role of Climate and Urban Parameters in the Confirmed Cases of COVID-19 Based on Artificial Intelligence Applications," IJERPH, MDPI, vol. 17(10), pages 1-21, May.
    6. Saravanan Venkatachalam & Arunachalam Narayanan, 2016. "Efficient formulation and heuristics for multi-item single source ordering problem with transportation cost," International Journal of Production Research, Taylor & Francis Journals, vol. 54(14), pages 4087-4103, July.

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