<![CDATA[Distribution networks must simultaneously optimize transport costs, travel time, service performance, vehicle utilization, fuel consumption, and carbon emissions to achieve sustainable logistics operations. Balancing these interrelated performance dimensions remains a significant challenge, particularly in regional distribution systems where operational data are often heterogeneous and limited. This study presents a descriptive evaluation of sustainable logistics performance using two complementary academic datasets representing a regional logistics context connecting Aceh and North Sumatra, Indonesia. The first dataset comprises ten paired conventional and optimized route scenarios, while the second consists of twelve-monthly operational observations including shipment volume, total logistics cost, on-time delivery performance, carbon emissions, fuel consumption, and vehicle load factor. Comparative analysis of the paired route scenarios indicates that total transportation costs decreased from IDR 12,933.0 thousand to IDR 10,437.0 thousand, representing a 19.30% reduction. Reported carbon emissions declined from 3,024.8 kg to 2,147.0 kg (29.02%), while total travel time decreased from 59.5 hours to 49.6 hours (16.64%). The monthly operational dataset records 2,583 shipments, with an average on-time delivery rate of 87.26%, mean carbon emissions of 21.35 tons, average fuel consumption of 12,542 liters, and a mean vehicle load factor of 71.53%. Because the paired route scenarios and monthly operational records do not share a common optimization protocol, deployment timeline, or route frequency, they are analyzed independently to avoid unsupported causal interpretations. The findings therefore identify favorable operational patterns rather than causal effects of network optimization. This study contributes a transparent evaluation framework that integrates route-level cost, emissions, and travel-time indicators with monthly service, fuel-efficiency, and loading-performance metrics, providing a practical decision-support approach for sustainable logistics management and future performance benchmarking]]>
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