Supply Chain Optimization for Natural Gas Installation Using Dynamic Programming and Markov Chains

de Jesus Rodriguez-Meza A.; Ñiquen-Levy R.; Eugenia Ferrua M.; del Carmen Tello Llaguento J.; Mantilla Segura J.; Novoa Marchena G.; Gianfranco Rodriguez iturrizaga E. · Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology (2026) · DOI: 10.18687/laccei2026.1.1.846

Resumen

This paper presents a hybrid decision-making model for optimizing the material supply chain in natural gas internal installations, focusing on companies providing installation services for condominiums and residential projects in Peru. Addressing the problem of recurring cost overruns-where empirical purchasing practices regularly exceeded the standard budget of USD 29,700 for 100-unit projects- a Deterministic Dynamic Programming (DDP) algorithm based on Bellman's optimality principle was implemented for optimal supplier selection, complemented by Markov Chains to assess operational resilience. Applied to a pilot project in the Miraflores district, the DDP model achieved a 28.35% cost reduction, optimizing procurement from the standard budget of USD 29,700 to USD 21,280 while ensuring a 20-day supply lead time. The optimal supplier sequence (Supplier 2 for meters → Supplier B for HDPE pipes → Supplier X for accessory kits) demonstrates a return on investment (ROI) of 38%, yielding potential annual savings of USD 84,200 for firms executing 10 projects per year. Additionally, Markov chain analysis identified a steady-state compliance probability of 70.9% and a failure risk of 6.0%, highlighting the need for contingency management. Considering that Peru's construction sector plans to scale production from 60,000 to 200,000 annual housing units, with 60% penetration in gasified zones (120,000 units), the potential market for gas installations would reach USD 71.9 million annually. This approach enables small and medium-sized enterprises (SMEs) in the sector to transition from empirical planning to data-driven scientific management, ensuring financial and operational sustainability in large-scale residential projects.

Instituciones: Universidad Privada del Norte