In medium and long-haul routes, stopover routes are defined as flights that make brief stops in a certain region during their journey, which can enhance seat occupancy rates, ensure more passengers are accommodated, and are considered crucial for the rational allocation of resources. Current research on route optimization commonly adopts the method of removing stopover points and modifying departure and arrival points under a single objective, which results in the passenger demand at stopover points being overlooked, leading to high optimization costs and increased difficulty. To address the optimization problem of flight stopover points, the five major hub airport groups within the three southwestern provinces and one municipality were taken as the research object, and a bi-objective optimization model was established to maximize user satisfaction and decision-maker benefits. Unlike traditional fixed algorithms, an improved heuristic algorithm, the whale optimization algorithm (WOA), was employed to solve the model, which was adapted to the study of stopover point optimization. Through empirical analysis of the stopover points in the domestic trunk route network, it is demonstrated that each optimized stopover route is increased by four alternative stopover points, passenger satisfaction is improved by 17.55%, and airline benefits are increased by 6.64%. By considering the trade-offs from both the decision-maker's and the user's perspectives, the coverage of routes and the connectivity of flights are effectively enhanced.