A Multiobjective Mixed‐Fleet Location Routing Model With Time Windows and Charging Infrastructure Decisions

This research addresses a multiobjective mixed‐fleet location routing problem with time windows. It combines routing, energy management, and charging infrastructure within a single mathematical framework. The problem is formulated as a mixed‐integer linear programming (MILP) model. The formulated MILP incorporates vehicle routing, time‐window constraints, and energy/fuel propagation dynamics. To solve this problem, and due to the NP‐hard nature of the proposed model, a hybrid solution methodology is developed. A multiobjective evolutionary algorithm is designed for scalable solution generation and the MILP formulation is proposed for validating solutions obtained. Computational experiments have shown the effectiveness of our approach to produce Pareto‐optimal solutions. The Pareto solutions has made it possible to analyze the trade‐offs between operational cost, infrastructure investment, and energy cost characteristics that aids on discussing the mathematical structure of integrated routing‐location problems.