Affiliation of Author(s):计算机科学与技术学院/人工智能学院/软件学院
Journal:Lect. Notes Comput. Sci.
Abstract:The present paper proposes a Greedy based Pareto Local Search (GB-PLS) algorithm for the bi-objective robust airport gate assignment problem (bRAGAP). The bRAGAP requires to minimize the total passenger walking distance and the total robust cost of gate assignment. The robust cost is measured through our proposed evaluation function considering the impact of delay cost on the allocation of idle time. GB-PLS uses the Random and Greedy Move (RGM) as a neighborhood search operator to improve the convergence and diversity of the solutions. Two populations are maintained in GB-PLS: the external population (EP) stores the nondominated solutions and the starting population (SP) maintains all the starting solutions for Pareto local search (PLS). The PLS is applied to search the neighborhood of each solution in the SP and the generated solutions are used to update the EP. A number of extensive experiments has been conducted to validate the performance of GB-PLS over Pareto Simulated Annealing (PSA). © Springer International Publishing AG 2017.
ISSN No.:0302-9743
Translation or Not:no
Date of Publication:2017-01-01
Co-author:Sun, Wenxue,Xia, Chao,Sulaman, Muhammad,M&#,s&#,r, Mustafa,Fan, Zhun
Correspondence Author:czz
Date of Publication:2017-01-01