In order to deal with Aircraft Recovery effectively for airlines, the classic Resource Assignment Model is expanded by broadening aircraft flow balance constraint and adding flights merger strategy. Besides, integrating the characteristics of Greedy Random Adaptive Search Procedure and Simulated Annealing algorithm, a new Greedy Random Simulated Annealing Algorithm is presented, which reduces the probability of getting a local optimal solution and improves the operating efficiency through restricting the types of aircraft route pairs and the number of candidate solutions. Empirical results demonstrate the ability of the new model and algorithm to quickly explore a wide range of unbalanced scenarios and to produce an optimal or near-optimal solution in time.
Optimization Model and Algorithm of Unbalanced Aircraft Recovery
Second International Conference on Transportation Engineering ; 2009 ; Southwest Jiaotong University, Chengdu, China
2009-07-29
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
Optimization Model and Algorithm of Unbalanced Aircraft Recovery
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