Optimal Restoration Scheduling of Damaged Networks Under Uncertain Environment by Using Improved Genetic Algorithm

被引:1
|
作者
Hitoshi FURUTA
Ken ISHIBASHI
Koichiro NAKATSU
Shun HOTTA
机构
[1] Department of Informatics, Kansai University
[2] Graduate School of Informatics, Kansai University
关键词
restoration schedule; genetic algorithm; uncertainty; delay of schedule;
D O I
暂无
中图分类号
TP399-C3 [];
学科分类号
081203 ; 0835 ;
摘要
The purpose of this research is to propose an early restoration for lifeline systems after earthquake disasters. The previous researches show that the optimization of the restoration schedule by using genetic algorithm (GA) is powerful. However, those are not considering the uncertain environment after earthquake disasters. The circumstances of the damage at devastated areas are very changeable due to the aftershock, fire disaster and bad weather. In addition, the restoring works may delay by unexpected accidents. Therefore, it is necessary to obtain the restoration schedule which has robustness, because the actual restoring works could not progress smoothly under the uncertain environment. GA considering uncertainty (GACU) can treat various uncertainties involved, but it is difficult to obtain the robust schedule. In this study, an attempt is made to develop a decision support system of the optimal restoration scheduling by using the improved GACU.
引用
收藏
页码:400 / 405
页数:6
相关论文
共 50 条
  • [41] Service restoration in compensated distribution networks using a hybrid genetic algorithm
    Augugliaro, A
    Dusonchet, L
    Sanseverino, ER
    ELECTRIC POWER SYSTEMS RESEARCH, 1998, 46 (01) : 59 - 66
  • [42] An Improved Genetic Algorithm for Task Scheduling of Electro-magnetic Detection Satellite with Uncertain Detecting Duration
    Zhang Lining
    Li Haoping
    Qiu Dishan
    Zhu Jianghan
    2009 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN AND CYBERNETICS (SMC 2009), VOLS 1-9, 2009, : 5128 - +
  • [43] An improved genetic algorithm on hybrid information scheduling
    Li J.
    Tian Q.
    Zheng F.
    Wu W.
    Recent Patents on Engineering, 2019, 13 (04) : 416 - 423
  • [44] Optimal construction of local model networks using genetic algorithm
    Sharma, SK
    Irwin, GW
    McLoone, S
    NEW TECHNOLOGIES FOR COMPUTER CONTROL 2001, 2002, : 559 - 564
  • [45] An improved genetic algorithm for the flowshop scheduling problem
    Rajkumar, R.
    Shahabudeen, P.
    INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, 2009, 47 (01) : 233 - 249
  • [46] Optimal design of water networks using fuzzy genetic algorithm
    Amirabdollahian, Mahsa
    Chamani, Mohammad Reza
    Asghari, Keyvan
    PROCEEDINGS OF THE INSTITUTION OF CIVIL ENGINEERS-WATER MANAGEMENT, 2011, 164 (07) : 335 - 346
  • [47] Optimal Scheduling of Time-Sensitive Networks for Automotive Ethernet Based on Genetic Algorithm
    Kim, Hyeong-Jun
    Lee, Kyung-Chang
    Kim, Man-Ho
    Lee, Suk
    ELECTRONICS, 2022, 11 (06)
  • [48] Coordinated Charging Scheduling for Electric Vehicles and Optimal Tuning of the Controller for Frequency Regulation under Uncertain Environment
    Das, Sourav
    Acharjee, Parimal
    Bhattacharya, Aniruddha
    2021 IEEE INDUSTRY APPLICATIONS SOCIETY ANNUAL MEETING (IAS), 2021,
  • [49] An optimal batch scheduling algorithm for OBS networks
    Figueiredo, Gustavo B.
    Xavier, Eduardo C.
    da Fonseca, Nelson L. S.
    GLOBECOM 2009 - 2009 IEEE GLOBAL TELECOMMUNICATIONS CONFERENCE, VOLS 1-8, 2009, : 111 - 116
  • [50] Optimal service restoration and reconfiguration of network using Genetic-Tabu algorithm
    Shin, DJ
    Kim, JO
    Kim, TK
    Choo, JB
    Singh, C
    ELECTRIC POWER SYSTEMS RESEARCH, 2004, 71 (02) : 145 - 152