Optimizing Sustainable Coal Hauling Under Uncertainty: A Multi-Stage Decision Tree Approach for a Palembang-Based Subcontractor

Abstract

This study develops a multi-stage decision tree model to optimize coal hauling operations for PT Baseline Business Control (PT BBC), a Palembang-based subcontractor facing weather uncertainty, strict ESG requirements, and thin profit margins. The model sequences four key decisions: route selection, fleet composition, driver productivity targets, and weather conditions, with a calibrated 30% probability of rain-induced full operational stoppages. Using data from management workshops and anonymized company records, six operational scenarios were evaluated on a 10-truck scale. The analysis combined Expected Monetary Value (EMV) through backward induction, Net Present Value (NPV) at a 5% discount rate, and Break-Even Point (BEP). Scenario 1, which uses the BSE–EPI PORT route, a 75% new / 25% old fleet mix, and an incentivized 17 trips per month target, emerged as the best option. It delivers the highest EMV of IDR 3.366 billion, a break-even period of 2.68 years, and an 18% reduction in CO₂ emissions intensity while achieving full ESG compliance. Sensitivity analysis using tornado and spider diagrams confirms that this strategy remains robust even under ±20% changes in coal price or rain probability. The findings show that selective fleet renewal combined with productivity incentives can effectively balance profitability, capital efficiency, and sustainability. This practical decision framework can be adapted by other coal hauling subcontractors across Indonesia and similar emerging markets.