A novel decision support framework for multi-objective aircraft routing problem

Abstract

The aircraft routing problem has received extensive attention from researchers, prompting the utilization of diverse problem-solving approaches and the use of various metrics to inform decision-making. Despite the wealth of research, airline managers often rely heavily on their own experience when evaluating potential aircraft routing solutions. To bridge this gap and empower airline managers with a robust decision-making process, this paper proposes a novel modeling framework and decision support tool for solving the Multi-Objective Aircraft Routing Problem. Our methodological framework comprises 3 modules: (i) an efficient data handling and storage process to manage a large volume of data and ensure data tractability; (ii) a novel mixed-integer linear programming model to effectively solve the aircraft routing problem within 1 to 5 min of computation, even at large instances; (iii) a multi-objective algorithmic framework that effectively employs parallelization techniques to generate Pareto-optimal frontiers within 30 min of computation. The three components are integrated into an unified decision support tool that empowers airline managers to visualize and evaluate various aircraft routing solutions, considering multiple objectives simultaneously while leveraging the use of multi-criteria methods. To validate the proposed approach, historic data from AirAsia is used for testing. The results demonstrate the tool’s capability to generate high-quality solutions that strike a balance between conflicting objectives, affirming its practicality and effectiveness in real-world applications.