Comparative Analysis of Conventional (Financial, Network) and Optimized Mixed Integer Linear Programming Scenarios for Telecom Network Investment Decision Making

Authors

  • Adithya Yudha Management, Faculty of Economics and Business, Universitas Telkom
  • Irni Yunita Management, Faculty of Economics and Business, Universitas Telkom

DOI:

https://doi.org/10.59141/jrssem.v4i3.734

Keywords:

MILP, CAPEX, OPEX, Optimization, Telecommunication

Abstract

The telecommunications industry in Indonesia faces numerous challenges in allocating resources for network development, including network complexity, technological changes, market competition, and customer expectations. To achieve optimal financial outcomes and customer satisfaction, investments must be well-managed, well-placed, and well-executed. This study analyses network investment portfolio selection outcomes at Telkomsel; Indonesia's largest cellular operator, comparing conventional scenarios (financial and network) with an optimized scenario using Mixed Integer Linear Programming (MILP). The research evaluates these scenarios based on total portfolio score, incremental revenue, and Internal Rate of Return (IRR). Financial indicators such as net present value (NPV), IRR, EBIT margin, incremental revenue, and network indicators such as capacity and customer satisfaction (download/upload throughput, latency, packet loss, jitter) assess investment feasibility. The MILP optimization scenario strongly correlates with incremental revenue, NPV, and IRR, indicating higher financial performance. Sites selected in the MILP optimization outperscenario formed others in total score (22% better than the financial scenario, 63% better than the network scenario), incremental revenue (3.5% better than the financial scenario, 90.2% better than the network scenario), and portfolio IRR (4% better than the financial scenario, 70% better than the network scenario). 

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Published

2024-10-15

How to Cite

Yudha, A., & Yunita, I. . (2024). Comparative Analysis of Conventional (Financial, Network) and Optimized Mixed Integer Linear Programming Scenarios for Telecom Network Investment Decision Making. Journal Research of Social Science, Economics, and Management, 4(3), 318–338. https://doi.org/10.59141/jrssem.v4i3.734