ABSTRACT
Aiming at the particularity of armored equipment maintenance spare parts such as many kinds, short maintenance task time and limited resources, a reasonable armored equipment maintenance resource optimization scheduling model is constructed, and the improved NSGA-2 algorithm is used for simulation calculation. The calculation results show that the algorithm can solve the problem of human resource conflict in the maintenance process, shorten the maintenance period of equipment, and optimize the scheduling of human resources in the maintenance process.
- Ya-Hong, Z., Ji-Ping, C., Zheng-Yuan, W., & Chang-Jiang, L. 2014. Optimal deployment of equipment maintenance support resources based on variable precision rough set in wartime. Fire Control & Command Control.39(06):40--44.Google Scholar
- Ji-Ping, C., Jian-She, S., Jun, G., & Jian-Ping, L. 2007. Optimization dispatching arithmetic of equipment maintenance support resources in wartime. Journal of System Simulation, 19(15), 3390--3394.Google Scholar
- Liang-Hua, X., & Chuan-Xin, G. 2004. Research of flexible assignment for equipment support resources. Journal of Institute of Command & Technology. (03):30--32Google Scholar
- Deb, K. 2002. A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Transactions on Evolutionary Computation, 6. Google ScholarDigital Library
- Liu, A. J., Yang, Y., Cheng, W. M., Xing, Q. S., & Yao, H. 2012. Improved NSGA for complex manufacturing environment. Jisuanji Jicheng Zhizao Xitong/Computer Integrated Manufacturing Systems, CIMS, 18(11), 2446--2458.Google Scholar
- Yi, H., En-Lin, Y. U., Xue-Wen, X. U., & Chun-Ting, S. 2015. Optimization of longitudinal welding parameters based on non-dominated sorting genetic algorithm. Journal of Yanshan University. 39(05):403--407.Google Scholar
- Hui-Na, Y., & Gang, L. 2013. Optimization design of high-power electronic transformer based on NSGA-II. Journal of North China Electric Power University.40(05):31--35.Google Scholar
- Sadrzadeh, A. 2012. A genetic algorithm with the heuristic procedure to solve the multi-line layout problem. Computers & Industrial Engineering, 62(4), 1055--1064. Google ScholarDigital Library
Index Terms
- Optimization Modeling and Decision Making of Equipment Maintenance Resource Scheduling Based on NSGA-2 Algorithm
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