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Efficient algorithms for cellular manufacturing systems with deterioration effect and inventory (case study: stone paper factory)

Mostafa Jafari & Amir Hossein Akbari

International Journal of Industrial and Systems Engineering2026https://doi.org/10.1504/ijise.2026.152157article
AJG 1
Weight
0.50

What the paper says

This research investigated the order acceptance and scheduling problem in CMS with tardiness cost, the deterioration effects of machines, and the cost of ordering and holding raw materials. Received orders have revenue, processing time, due date, tardiness cost, and decisions about acceptance or rejection are made. We have proposed a linear programming mathematical modelling with objective profit maximisation. Due to the NP-hard nature of the problem, a meta-heuristic algorithm based on a genetic algorithm is introduced to solve large dimensions. The proposed model has been tested in four modes: CODH, COFH (removal of the deterioration effect of the machine), CODI (the removal of holding and ordering raw), and CSDH (removal of acceptance and scheduling of all orders). The results show the performance of the proposed algorithm. The authors' findings help managers to make better decisions, improve supply chain actions, enhance competitive advantage, enhance customer satisfaction and attract more customers.

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https://doi.org/https://doi.org/10.1504/ijise.2026.152157

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@article{mostafa2026,
  title        = {{Efficient algorithms for cellular manufacturing systems with deterioration effect and inventory (case study: stone paper factory)}},
  author       = {Mostafa Jafari & Amir Hossein Akbari},
  journal      = {International Journal of Industrial and Systems Engineering},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1504/ijise.2026.152157},
}

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Efficient algorithms for cellular manufacturing systems with deterioration effect and inventory (case study: stone paper factory)

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.