Development of A Backorder P Model for Inventory Management Issues at PLN UID Suluttenggo Considering Revenue Losses

Authors

  • Syabar Iqramullah PT PLN (Persero), Indonesia
  • Lucia Diawati Master Program of Logistic, Institut Teknologi Bandung, Bandung 40123, Indonesia
  • Sukoyo Master Program of Logistic, Institut Teknologi Bandung, Bandung 40123, Indonesia

Keywords:

model p, back order, Two-echelon distribution, nonlinear programming (NLP), material allocation

Abstract

PT PLN (Persero) Distribution of North Sulawesi, Central Sulawesi and Gorontalo  (UID Suluttenggo) is committed to enhancing the reliability of its new customer connection services. Given the expansive and geographically dispersed operational area, a tiered procurement and material distribution system is implemented. The material distribution process begins at the supplier level and continues to the Customer Service Implementation Units (UP3), which serve as regional distribution warehouses, before being forwarded to Customer Service Units (ULP) based on fluctuating demand. This study aims to model the two-echelon distribution problem by incorporating potential revenue losses resulting from delayed fulfillment (backorders). The problem is formulated within the framework of a periodic inventory model (P-method) with backordering, which falls under the category of nonlinear programming (NLP). The proposed model enables the determination of the optimal ordering cycle and appropriate safety stock levels, with the objective of balancing ordering frequency, storage capacity, and customer service levels. A case study conducted at one of the ULPs in Suluttenggo demonstrates that this approach can lead to more efficient inventory ordering decisions.

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References

Abdelwahab, W. M., & Sargious, M. (1990). Modeling the demand for freight transport. Journal of Transport Economics and Policy, 24(2), 139–152. https://www.jstor.org/stable/20052741.

Russell, R. S. (1991). Operations Management: Creating Value Along the Supply Chain. Prentice Hall.

Zhao, X., Xie, J., & Zhang, W. J. (2004). The impact of demand uncertainty on supply chain performance: A simulation study. International Journal of Production Research, 40(1), 85–103.https://doi.org/10.1080/00207540310001618094.

Burhan. (2010). Model P Back Order dan Algoritma Permasalahan Inventori dengan Mempertimbangkan Ongkos Transportasi (Fixed and Variable Cost) – Permintaan Probabilistik. AGROINTEK, 4(2), 158–166.

Pulido-Rojano, A., Pizarro-Rada, A., Padilla-Polanco, M., SánchezJiménez, M., & De-la-Rosa, L. (2020). An Optimization Approach for

Inventory Costs in Probabilistic Inventory Models: A Case Study. Ingeniare. Revista Chilena de Ingeniería, 28(3), 383–395. https://doi.org/10.4067/S0718-33052020000300383.

Rini, M. W., & Ananda, N. (2021). Analisis kebijakan inventori probabilistik dengan model P-backorder dan Q-backorder. Journal

Industrial Servicess, 7(1), 1–7. http://dx.doi.org/10.36055/jiss.v7i1.12525:contentReference[oaicite:0]{index=0}

Putra, R. A., Widowati, W., Sutrisno, S., Azis, M. I., & Magdalena, I. (2023). Probabilistic Economic Order Quantity Model with P-Method and Backordering System for Multi-Product with Quantity Discount. AIP Conference Proceedings, 2738(1), 020014. https://doi.org/10.1063/5.0140162

Published

2025-10-29

How to Cite

Iqramullah, S., Diawati, L., & Sukoyo, S. (2025). Development of A Backorder P Model for Inventory Management Issues at PLN UID Suluttenggo Considering Revenue Losses. ITB Graduate School Conference, 5(1). Retrieved from https://gcs.itb.ac.id/proceeding-igsc/index.php/igsc/article/view/684