Multiproduct and multistage integrated production planning model and algorithm based on an available production capacity network

Zhi-min Lü; Tian-ru Jiang; Zai-wei Li

doi:10.1007/s12613-021-2310-6

Volume 28 Issue 8

Aug. 2021

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Article Navigation > International Journal of Minerals, Metallurgy and Materials > 2021 > 28(8): 1343-1352

Zhi-min Lü, Tian-ru Jiang, and Zai-wei Li, Multiproduct and multistage integrated production planning model and algorithm based on an available production capacity network, Int. J. Miner. Metall. Mater., 28(2021), No. 8, pp. 1343-1352. https://doi.org/10.1007/s12613-021-2310-6

Cite this article as:

Zhi-min Lü, Tian-ru Jiang, and Zai-wei Li, Multiproduct and multistage integrated production planning model and algorithm based on an available production capacity network, Int. J. Miner. Metall. Mater., 28(2021), No. 8, pp. 1343-1352. https://doi.org/10.1007/s12613-021-2310-6

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Research Article

Multiproduct and multistage integrated production planning model and algorithm based on an available production capacity network

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Corresponding author:
Zhi-min Lü E-mail: lvzhimin@nercar.ustb.edu.cn
Received: 28 February 2021; Revised: 27 May 2021; Accepted: 31 May 2021; Available online: 1 June 2021

Abstract

Abstract

This research attempts to devise a multistage and multiproduct short-term integrative production plan that can dynamically change based on the order priority and virtual occupancy for application in steel plants. Considering factors such as the delivery time, varietal compatibility between different products, production capacity of variety per hour, minimum or maximum batch size, and transfer time, we propose an available production capacity network with varietal compatibility and virtual occupancy for enhancing production plan implementation and quick adjustment in the case of dynamic production changes. Here available means the remaining production capacity after virtual occupancy. To quickly build an available production capacity network and increase the speed of algorithm solving, constraint selection and cutting methods with order priority were used for model solving. Finally, the genetic algorithm improved with local search was used to optimize the proposed production plan and significantly reduce the order delay rate. The validity of the proposed model and algorithm was numerically verified by simulating actual production practices. The simulation results demonstrate that the model and improved algorithm result in an effective production plan.
- short-term integrated plan;
- constraint satisfaction model;
- available production capacity;
- varietal compatibility;
- virtual capacity occupancy

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