Multiobjective Evolutionary Scheduling and Rescheduling of Integrated Aircraft Routing and Crew Pairing Problems

被引:17
作者
Chen, Chiu-Hung [1 ]
Chou, Fu-, I [2 ]
Chou, Jyh-Horng [3 ,4 ,5 ]
机构
[1] Feng Chia Univ, Dept Mech & Comp Aided Engn, Taichung 407, Taiwan
[2] Natl Formosa Univ, Dept Automat Engn, Huwei Township 632, Yunlin, Taiwan
[3] Natl Kaohsiung Univ Sci & Technol, Dept Elect Engn, Kaohsiung 807, Taiwan
[4] Natl Chung Hsing Univ, Dept Mech Engn, Taichung 402, Taiwan
[5] Kaohsiung Med Univ, Dept Healthcare Adm & Med Informat, Kaohsiung 807, Taiwan
关键词
Airline rescheduling; aircraft routing; crew pairing; integrated airline scheduling; multiobjective optimization; GENETIC ALGORITHM; BENDERS DECOMPOSITION; JOB-SHOP; OPTIMIZATION;
D O I
10.1109/ACCESS.2020.2974245
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper presents a multiobjective evolutionary approach that can solve integrated airline scheduling and rescheduling problems under conditions of disruption. The integrated problem simultaneously considers both aircraft routing and crew pairing to meet several objectives under real-world constraints and disturbance events. Because of their high complexity, we formulated integrated problems as combinational optimization problems and used the NSGA-II variant method combined with a repair strategy as the solver. To verify and validate the proposed approach, real-world flight data were used to build study cases. In the experiment, we first studied the convergence of the algorithm by using the repair method. We then reviewed real-world plans and evaluated the improvement obtained using the proposed integrated approach. Finally, a disruption was simulated to study rescheduling capability. Experimental results showed that the proposed approach yields better schedules than real-world expert-made plans and that Pareto solutions after the disruption can, under safety and legal constraints, be successfully explored in rescheduling problems.
引用
收藏
页码:35018 / 35030
页数:13
相关论文
共 45 条
[1]   Applications of operations research in the air transport industry [J].
Barnhart, C ;
Belobaba, P ;
Odoni, AR .
TRANSPORTATION SCIENCE, 2003, 37 (04) :368-391
[2]   An approximate model and solution approach for the long-haul crew pairing problem [J].
Barnhart, C ;
Shenoi, RG .
TRANSPORTATION SCIENCE, 1998, 32 (03) :221-231
[3]   Heuristic approaches for flight retiming in an integrated airline scheduling problem of a regional carrier [J].
Cacchiani, Valentina ;
Salazar-Gonzalez, Juan-Jose .
OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE, 2020, 91
[4]   Optimal Solutions to a Real-World Integrated Airline Scheduling Problem [J].
Cacchiani, Valentina ;
Salazar-Gonzalez, Juan-Jose .
TRANSPORTATION SCIENCE, 2017, 51 (01) :250-268
[5]   Energy-efficient bi-objective single-machine scheduling with power-down mechanism [J].
Che, Ada ;
Wu, Xueqi ;
Peng, Jing ;
Yan, Pengyu .
COMPUTERS & OPERATIONS RESEARCH, 2017, 85 :172-183
[6]   Integrated Short-Haul Airline Crew Scheduling Using Multiobjective Optimization Genetic Algorithms [J].
Chen, Chiu-Hung ;
Liu, Tung-Kuan ;
Chou, Jyh-Horng .
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2013, 43 (05) :1077-1090
[7]  
Chen CH, 2010, INT J INNOV COMPUT I, V6, P3943
[8]   Benders decomposition for simultaneous aircraft routing and crew scheduling [J].
Cordeau, JF ;
Stojkovic, G ;
Soumis, F ;
Desrosiers, J .
TRANSPORTATION SCIENCE, 2001, 35 (04) :375-388
[9]   A fast and elitist multiobjective genetic algorithm: NSGA-II [J].
Deb, K ;
Pratap, A ;
Agarwal, S ;
Meyarivan, T .
IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, 2002, 6 (02) :182-197
[10]   An Evolutionary Many-Objective Optimization Algorithm Using Reference-Point-Based Nondominated Sorting Approach, Part I: Solving Problems With Box Constraints [J].
Deb, Kalyanmoy ;
Jain, Himanshu .
IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, 2014, 18 (04) :577-601