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This paper addresses a competitive airline hub-and-spoke network design problem in a duopolistic market with sequential airline entry. Two airlines, a leader and a follower, enter the market sequentially to make decisions about their own flight networks. Each must consider their opponent's reactions and respond to each other's decisions in making their own, leading to interactive competition between them. A bi-level model is proposed to formulate the behaviors and decisions of the two airlines. In addition, an interactive solution procedure based on a genetic algorithm (GA) is developed to repeatedly solve the upper and lower level models. Finally, we generate a numerical example based on the regional air market in Taiwan and China. The results provide useful insights and highlight the importance of considering interactive competition for airlines when designing their flight networks. [ABSTRACT FROM AUTHOR]

Abstract: In this study, we develop a solution method for solving air express cargo loading problems under stochastic demands. The method is designed by combining the scenario decomposition and genetic algorithm (GA) techniques. Numerical tests are performed to evaluate the performance of the solution method using data for the Asian operations of an international express carrier. The results show that the solutions obtained from our method are very close to the optimal solutions. Furthermore, our method has an advantage in terms of computation time over the CPLEX optimization algorithm. [Copyright &y& Elsevier]