Enhanced Multi-Objective Green Vehicle Routing with a New Fuzzy Speed-Driven Fuel Consumption Model - Kayij Nawej, Emile; Mangongo, Yves Tinda; Kafunda, Pierre Katalay; Kampempe, Justin-Dupar Busili (Journal of Applied Informatics and Computing, 2026)
Today, decision-makers begun to prioritize the concept of green logistics, which is based on strategies aimed to promote more environmentally sustainable practices during vehicle routing. Among key factors influencing fuel consumption in such problems, vehicle speed plays a crucial role. This article adapts the Comprehensive Modal Emission Model (CMEM) for fuel consumption by treating vehicle speed as a fuzzy variable. This enhanced version, referred as Fuzzy-CMEM, enables the formulation of a more realistic fuzzy multi-objective Green Vehicle Routing Problem (GVRP). The proposed methodology follows four main steps. First, we formulate the problem considering the vehicle speed as a fuzzy variable. Second the initial fuzzy problem is defuzzified using the interval approximation approach. Third, a sequential approach is adopted where the sweep heuristic is used to construct feasible routes, and the BicriterionAnt metaheuristic is employed to generate optimal Pareto-front solutions of the resulting deterministic problem. Finally, a numerical simulation is addressed, followed by a comparative analysis of results and discussion.