A Mixed Integer Linear Programming (MILP) model for Non-strict Uncapacitated Multi-allocation p-hub Median Problem (NSUMApHUMP) is established. Applied genetic algorithm to the hub and spoke locations to minimize the total costs of airline network. Exact solutions of the model are obtained by encoding individual structure correctly and improving genetic operator according to this MILP model and hub-and-spoke network configuration. The instance analysis validates strong feasibility of the model and high efficiency of the proposed genetic algorithm for NSUMApHUMP.

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This paper focuses on the issue of planning and optimization of airline network under PRD (Prohibited Area, Restricted Area and Danger Area) avoiding, in a way of hierarchical and quantitative design. According to the principle of Maklink Graph method, the issue of optimization of airline network was transformed to the issue of optimization of non-interference path point distribution. A method of addition of virtual path point was proposed to solve the problem of traffic jam in the airlines, and a Differential Evolution Algorithm was adopted to solve the model of the virtual path point distribution. In the end, a few representative performance indexes were chosen to evaluate the optimized airline network, and the evaluation result has proved that the method proposed in this paper to plan and optimize the airline network was reasonable and effective.