Mathematical Models, GRASP Algorithms and Fitness Landscape Analysis for Aircraft Gate Assignment Problem

The assignment of the airline planes to appropriate gates is complex combinatorial optimization. Most of the research works in previous literatures take the passengers´ walking distance as the optimization objective. With the development of the air transportation, more and more transferring services are required. In this paper, a novel AGAP model is developed to meet this demand. A number of heuristic algorithms have been proposed to solve the AGAP. Those heuristics have the disadvantages of slow convergence and precocity, which affect the performance of the algorithms. The GRASP procedures have a series of good features: strong intuitive greedy appeals, prominent empirical track records, and trivial to be efficiently implemented on parallel processors. More important, GRASP can overcome the precocity. In this paper, a GRASP algorithm on AGAP is proposed to solve the AGAP problem. Experimental results demonstrate that our GRASP algorithm on AGAP evidently exceeds GA algorithms on the quality of solutions and time complexity. To explain why GRASP algorithm on AGAP has a better performance than GA, fitness landscape analysis is presented.