Application of Improved SAGA Algorithm in Substation Inspection Job Scheduling

doi:10.3969/j.issn.1006-2475.2016.11.020

Abstract

Abstract: Against the substation inspection operation scheduling problem under the condition of multi-resource constraints, according to the location of the inspection members, the current mission, the mission details, the tasks to be implemented, inspection equipment, historical inspection records and other factors, we built a mathematical model, and put forward an improved genetic algorithm. The algorithm solves the problem that the traditional genetic algorithm falls into the local optimal solution, and has the characteristics of fast convergence speed. The experimental results show that the SAGA algorithm is superior to GA algorithm to solve substation inspection job scheduling problem, and has higher calculation efficiency.


Key words: job scheduling, substation inspection, genetic algorithm, simulated annealing arithmetic

CLC Number:

TP301.6

XIE Xiao-jun1, ZHUO Wen-he1, HU Peng2. Application of Improved SAGA Algorithm in Substation Inspection Job Scheduling[J]. Computer and Modernization, doi: 10.3969/j.issn.1006-2475.2016.11.020.

References

［1］吴婉彬,汪晨,张贾军. 基于移动作业的变电站巡检方法［J］. 通信电源技术, 2015,32(6):246-249.
［2］周盼,张蕾. 基于Android平台的变电站智能巡检系统［J］. 计算机测量与控制, 2015,23(9):3073-3076.
［3］戴上平,高丽,朱长武. 基于遗传模拟退火算法的任务分配与调度［J］. 广西师范大学学报(自然科学版), 2006,24(4):151-154.
［4］钟求喜,谢涛,陈火旺. 基于遗传算法的任务分配与调度［J］. 计算机研究与发展, 2000,37(10):1197-1203.
［5］武兆慧,张桂娟,刘希玉. 基于模拟退火遗传算法的聚类分析［J］. 计算机应用研究, 2005,22(12):24-26.
［6］罗晨,李渊,刘勇,等. 基于模拟退火遗传算法的多Agent系统任务分配［J］. 计算机应用研究, 2012,29(6):2114-2116.
［7］程晖. 基于遗传模拟退火的服装排料算法的研究［D］. 上海:东华大学, 2012.
［8］吴鑫淼. 面向移动作业的供电公司排班调度优化模型及算法研究［D］. 杭州:杭州电子科技大学, 2013.
［9］章坚民,吴鑫淼,陈耀军,等. 供电公司移动作业排班调度优化模型及算法［J］. 电力系统自动化, 2013,37(14):81-88.
［10］郭建,苏玲. 遗传—模拟退火混合算法在配电网检修优化中的应用［J］. 陕西电力, 2011,39(6):44-46.
［11］温步瀛. 发电机组启停机计划的智能优化研究［D］. 福州:福州大学, 2006.
［12］Yoshikawa M, Yamauchi H, Terai H. Hybrid architecture of genetic algorithm and simulated annealing［J］. Engineering Letters, 2008,16(3):339-345.
［13］刘思革,程浩忠,崔文佳. 基于粗糙集理论的多目标电网规划最优化模型［J］. 中国电机工程学报, 2007,27(7):65-69.
［14］Zeng Bin, Wei Jun, Wang Wei, et al. Cooperative grid jobs scheduling with multi-objective genetic algorithm［C］// Proceedings of the 5th International Conference on Parallel and Distributed Processing and Applications. 2007:545-555.
［15］周鑫. 分布式数控系统车间排产系统的设计与实现［D］. 沈阳:中国科学院研究生院（沈阳计算技术研究所）, 2014.
［16］蒋美云. 遗传模拟退火算法在云调度中的应用研究［J］. 计算机与现代化, 2013(6):38-41.
［17］周鑫,马跃,胡毅. 求解车间作业调度问题的混合遗传模拟退火算法［J］. 小型微型计算机系统, 2015(2):370-374.

[1]	LIU Xian-zhuo, DENG Wei-si, XIE En-yan. Adaptive Protection System for Distribution Network Considering Grid Connection of Distributed Generation [J]. Computer and Modernization, 2023, 0(09): 120-126.
[2]	ZHANG Zhi-xia, XIE Bao-qiang. Natural Gas Load Forecasting Based on FCGA-LSTM and Transfer Learning [J]. Computer and Modernization, 2023, 0(07): 7-12.
[3]	WANG Min, XU Ying-hao, ZHU Xi-jun. Prediction Model of Diabetic Complications Based on BP Neural Network Optimized by Improved Genetic Algorithm#br# [J]. Computer and Modernization, 2022, 0(11): 69-74.
[4]	WANG Yang, CHEN Mei, LI Hui. FOCoR: A Course Recommendation Approach Based on Feature Selection Optimization [J]. Computer and Modernization, 2022, 0(10): 1-7.
[5]	RAN Hao-jie, WANG Hong-zhi. Distribution Center Site Selection of Fresh Agricultural Products Based on Improved Simulated Annealing Algorithm [J]. Computer and Modernization, 2022, 0(10): 36-40.
[6]	ZHAN Jun-wei, ZHUANG Yi. Mobile Edge Computing Task Offloading Model and Algorithm Based on Energy Consumption and Delay Optimization [J]. Computer and Modernization, 2022, 0(08): 86-93.
[7]	WU Dai-yang, ZHAO Jie, LIANG Jia-ming, DONG Zhen-ning, LIANG Zhou-yang. Host Matching for C2C Online Short-term Rentals [J]. Computer and Modernization, 2022, 0(06): 43-48.
[8]	XU Sheng-chao, XIONG Mao-hua. Optimization of Container Cloud Resource Allocation Based on Genetic Algorithm [J]. Computer and Modernization, 2022, 0(01): 108-112.
[9]	XU Ming, ZHANG Jian-ming, CHEN Song-hang, CHEN Hao. Multi-objective Optimization Algorithm for Flexible Job Shop Scheduling Problem [J]. Computer and Modernization, 2021, 0(12): 1-6.
[10]	ZHANG Lin-peng, WANG Xi-yuan, LI Qiang. Image Classification Based on Double-pooling Feature Weighted Convolutional Neural Network [J]. Computer and Modernization, 2021, 0(11): 67-71.
[11]	YANG Xiao-dong. Risk Assessment Model of Accounting Resource Sharing Management Based on Genetic Algorithm [J]. Computer and Modernization, 2021, 0(06): 24-28.
[12]	LIU Jun, PENG Hui-xian, HUANG Bin, Tony SHAY. Breast Cancer Diagnosis Model Based on BP-GamysBoost [J]. Computer and Modernization, 2021, 0(04): 8-14.
[13]	XU Sheng-chao. Using Genetic Algorithm for Virtual Machine Placement Optimization [J]. Computer and Modernization, 2020, 0(12): 25-31.
[14]	WU Hai-wei, WANG Xiao-zhong, ZHU Fa-shun, . A Scheduling Method of Smart Grid Based on Genetic Algorithm [J]. Computer and Modernization, 2020, 0(09): 122-126.
[15]	ZHANG Zhi-wei, GAN Gang. Service Vulnerability Mining of Android System Based on Genetic Algorithm [J]. Computer and Modernization, 2020, 0(08): 114-121.