The ALNS Metaheuristic for the Maintenance Scheduling Problem

被引:2
作者
Woller, David [1 ,2 ]
Kulich, Miroslav [1 ]
机构
[1] Czech Tech Univ, Czech Inst Informat Robot & Cybernet, Jugoslavskych Partyzanu 1580-3, Prague 16000 6, Czech Republic
[2] Czech Tech Univ, Fac Elect Engn, Dept Cybernet, Karlovo Namesti 13, Prague 12135 2, Czech Republic
来源
PROCEEDINGS OF THE 18TH INTERNATIONAL CONFERENCE ON INFORMATICS IN CONTROL, AUTOMATION AND ROBOTICS (ICINCO) | 2021年
关键词
Adaptive Large Neighborhood Search; Metaheuristics; Combinatorial Optimization; Maintanance Scheduling; ROADEF; 2020; GENERATING-UNITS; OPTIMIZATION; ALGORITHM;
D O I
10.5220/0010552101560164
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Transmission maintenance scheduling (TMS) is an important optimization problem in the electricity distribution industry, with numerous variants studied and methods proposed over the last three decades. The ROADEF challenge 2020 addresses a novel version of the TMS problem, which stands out by having multiple timedependent properties, constraints, and a risk-based aggregate objective function. Therefore, the problem is more complex than the previous formulations, and the existing methods are not directly applicable. This paper presents a method based on the Adaptive Large Neighborhood Search metaheuristic. The method is compared with the best-known solutions from the challenge qualification phase, in which more than 70 teams participated. The result shows that the method yields consistent performance over the whole dataset, as the method finds the best-known solutions for half of the dataset and finds solutions consistently within 5h gap.
引用
收藏
页码:156 / 164
页数:9
相关论文
共 24 条
[1]   Source and transmission line maintenance outage scheduling in a power system using teaching learning based optimization algorithm [J].
Abirami, M. ;
Ganesan, S. ;
Subramanian, S. ;
Anandhakumar, R. .
APPLIED SOFT COMPUTING, 2014, 21 :72-83
[2]  
Boruvka Otakar, 1926, Prace moravske prirodov.edecke. spolecnosti., V3, P37
[3]   Hybrid evolutionary techniques for the maintenance scheduling problem [J].
Burke, EK ;
Smith, AJ .
IEEE TRANSACTIONS ON POWER SYSTEMS, 2000, 15 (01) :122-128
[4]   Generation maintenance scheduling considering transmission constraints [J].
da Silva, EL ;
Schilling, MT ;
Rafael, MC .
IEEE TRANSACTIONS ON POWER SYSTEMS, 2000, 15 (02) :838-843
[5]  
Duarte A, 2018, HDB HEURISTICS, P341, DOI [10.1007/978-3-319-07124-49, DOI 10.1007/978-3-319-07124-4_9, 10. 1007/978-3-319-07124-4_9, 10.1007/978-3-319-07124-4, DOI 10.1007/978-3-319-07124-4]
[6]   Clonal selection algorithm for power generators maintenance scheduling [J].
El-Sharkh, M. Y. .
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2014, 57 :73-78
[7]   Optimal maintenance scheduling of power producers considering unexpected unit failure [J].
Feng, C. ;
Wang, X. ;
Li, F. .
IET GENERATION TRANSMISSION & DISTRIBUTION, 2009, 3 (05) :460-471
[8]   Maintenance scheduling in the electricity industry: A literature review [J].
Froger, Aurelien ;
Gendreau, Michel ;
Mendoza, Jorge E. ;
Pinson, Eric ;
Rousseau, Louis-Martin .
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2016, 251 (03) :695-706
[9]   Coordinated preventive maintenance scheduling of GENCO and TRANSCO in restructured power systems [J].
Geetha, T. ;
Swarup, K. Shanti .
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2009, 31 (10) :626-638