Multiobjective Optimization Genetic Algorithms for Domestic Airline Crew Pairing Problems
نویسندگان
چکیده
Airline crew pairing problems involve assigning the required crew members to each flight segment in a given time period, while complying with a variety of work regulations and collective agreements. Traditional researches formulate the pairing problems as integer programming problems, and use deterministic approaches to optimize the solutions. Such these approaches usually suffer from some critical issues such as time-consuming enumeration for possible pairings and difficulty to cover the whole search space. The goal of this paper is to develop a new multiobjective approach to solve the crew pairing problem by formulating it into multiobjective combination optimization equations and employing the inequality-based multiobjective genetic algorithm (MMGA) as the global optimization explorer. Besides, our experimental results for a real-world short-haul domestic airline show that the proposed approach can provide quite good pairing solutions.
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