Toward the optimization of fuel consumption on container-on-barge operations in river transportation

Abstract

The national policy for fuel prices in Colombia and the management of the fluvial route of the Magdalena River has led to effects on productivity and benefits for companies and maritime ports due to contracts for dredging that guarantee drafts for six months. Moreover, increases in fuel prices have generated higher operating costs than those of previous years. Data analysis is a crucial decision-making tool for operational-level decision-makers in companies, supported by the measures of indicators, competitiveness, and productivity in terminal services. The transportation and shipping of cargo entail significant costs in terms of fuel, labor, and time, as well as other costs that must be met for meeting customer commitments.This paper presents a methodology for fuel consumption optimization in the specific case of transportation by a Colombian river transportation company, using regression models and response-surface methodology as optimization tools. This approach yields significant results, reducing fuel consumption by approximately 25% through a combination of various factors involved in barge transportation operations, including labor, fuel, velocity, weight, and other operational aspects. The primary contribution of this research lies in its promotion of sustainable operations through cost reduction and the reduction of fuel consumption reduction. The use of statistical optimization techniques makes this methodology applicable to similar cases of shipping and transportation. It additionally addresses national policy changes related to emissions, fuel costs, and sustainability, thereby aligning with a focus on energy transition to promote cost reduction.